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A three-phase study was performed to examine abiotic and biotic metrics at southern pine beetle infestation sites in northern Georgia in 2002 to find early indicators that can be leveraged by forest managers to mitigate the effects of future outbreaks: creation of a 2003 Final Impact Map, determining if MODIS MOD13Q1 EVI 16-day image composites can distinguish differences in biomass indicators among healthy and infested loblolly pine and hardwood forests, and creation of an Infestation Risk Map derived from significant climate and physical variables at known infestation sites.Three land cover classification techniques (change vector analysis, enhanced wetness differencing index and standard land cover classification analysis of Landsat 5 TM) were compared to determine which would provide the best estimate of final infestation damage. Classification accuracy results indicated that the latter provided the most reliable site damage information and it became the reference map against which outbreak model results were compared.Using time series analysis of MODIS composites acquired March 2000 - December 2006 to measure 11 phenology metrics for infested and healthy loblolly and hardwood stands showed that the imagery differentiated between forest classes. Results indicated the lowest base vegetation biomass in 2001 for infested loblolly, relative to healthy loblolly, with many metrics trending towards hardwood values following infestation.Abiotic influences included those related to landscape position and climate. Statistical testing showed increased beetle success: 1) along ridge tops at maximum solar exposure, 2) in areas with canopy density>60%, 3) in areas experiencing cooler summers and warmer winters, and 4) where precipitation was significantly lower at infested sites in the 2 years preceding outbreak.The Infestation Risk Map was developed from significant physical and climate indicator variables using the fuzzy theory modeling approach. Comparison of model output to infestation sites resulted in Chi-squared and Cramér's V values of 55.4 and 0.16, respectively, indicating that infestation risk distributions strongly paralleled site infestation. Comparison of model output and low, medium and high infestation density clusters resulted in Chi-squared and Cramér's V values of 241.24 and 0.66, respectively, indicating a more substantive relationship between infestation density and risk classes.

The Southern Pine Beetle, or SPB, (Dendroctonus frontalis Zimmerman) is a bark beetle that is endemic to the Southern forest ecosystem. Beetle populations remain stable for years at a time; however, for reasons not fully understood the beetle undergoes accelerated population growth on approximate ten-year cycles, culminating in increased beetle activity. Although most trees can withstand a beetle assault when populations are reduced, healthy trees, and even pine species that are not generally attacked can become a host tree for millions of beetles during infestations. Much of Appalachia was paralyzed by an unusually heavy snowstorm on January 27, 1998, resulting in major power failures and tremendous tree damage. Environmental hazards such as this storm have historically been a factor with southern pine beetle populations. This study hypothesizes that the blizzard of January 27, 1998, significantly increased the southern pine beetle population. The evidence, however, did not support this hypothesis.

Under normative conditions the mountain pine beetle (Dendroctonus ponderosae Hopkins) has played a regulating role in healthy lodgepole pine (Pinus contorta) forests. However, recently eruptive outbreaks that result from large pine beetle populations have destroyed vast tracts of valuable forest. The outbreaks in North America have received a great deal of attention from both the timber industry and government agencies as well as biologists and ecologists. In this dissertation we develop a landscape-scaled integrodifference equation model describing the mountain pine beetle and its effect on a lodgepole pine forest. The model is built upon a stage-structured model of a healthy lodgepole pine forest with the addition of beetle pressure in the form of an infected tree class. These infected trees are produced by successful beetle attack, modelled by response functions. Different response functions reflect different probabilities for various densities. This feature of the model allows us to test hypotheses regarding density-dependent beetle attacks. To capture the spatial aspect of beetle dispersal from infected trees we employ dispersal kernels. These provide a probabilistic model for finding given beetle densities at some distance from infected trees. Just as varied response functions model different attack dynamics, the choice of kernel can model different dispersal behavior. The modular nature of the Red Top Model yields multiple model candidates. These models allow discrimination between broad possibilities at the land scape scale: whether or not beetles are subject to a threshold effect at the lands cape scale and whether or not host selection is random or directed. We fit the model using estimating functions to two distinct types of data: aerial damage survey data and remote sensing imagery. Having constructed multiple models, we introduce a novel model selection methodology for spatial models based on facial recognition technology. Because the regions and years of aerial damage survey and remote sensing data in the Sawtooth National Recreation Area overlap, we can compare the results from data sets to address the question of whether remote sensing data actually provides insight to the system that coarser scale but less expensive and more readily available aerial damage survey data does not.

Ninety-four unmanaged lodgepole pine stands were examined to evaluate the relationship between stand density and susceptibility to mountain pine beetle attack. Sample included stands from a broad geographical range in the western United States. Beetle population trends were not significantly related to variation in stand density as measured by stand density index (SDI). The percentage of trees killed per acre by the mountain pine beetle in stands with greater than eighty percent lodgepole pine did vary significantly with changes in SDI. From these data three SDI zones were identified: 1) stands with SDI's of less than 125 showed low potential for attack, 2) stands between 125 and 250 SDI showed much greater levels of tree mortality, gradually decreasing toward the 250 SDI, 3) tree mortality decreased in stands as density increased beyond the 250 SDI value.

Mountain pine beetle (Dendroctonus ponderosae Hopkins) has caused extensive tree mortality in whitebark pine (Pinus albicaulis Engelm) forests. Previous studies conducted in various conifer forests have shown that fine surface fuels are significantly altered during a bark beetle outbreak. Bark beetle activity in conifer stands has also been shown to alter foliar fuel moisture content and chemistry over the course of the bark beetle rotation.The objective of this study was to evaluate changes to fine surface fuels, foliar fuel moisture and chemistry and litter chemistry in and under whitebark pine trees infested by mountain pine beetle. Fuels were measured beneath green (healthy) trees compared to red (two years since initial MPB attack with 50% or greater needles remaining) and gray (greater than two years since attack with between 15% and 45% needles remaining) trees. Foliar moisture content was measured in four mountain pine beetle crown condition classes: green-uninfested, green-infested (current year’s attack), yellow (last year’s attack), and red. Total terpene content was analyzed in whitebark pine needle litter and volatile terpenes were collected and analyzed from green, green-infested, yellow, and red trees.Significant differences were found in litter depths under green, red, and graytrees. Duff depths were significantly less beneath green trees than red and gray trees. One hour and ten hour fuels were more influenced by diameter and crown size than beetle crown condition classes. Foliar fuel moisture content dramatically decreased from green-infested to the red beetle crown condition class. No differences were detected in shrub and forb biomass between green, red, and gray trees. Green-infested trees had significantly lower foliar fuel moisture than green trees and by late in the season showed fuel moisture levels similar to red trees which had the lowest fuel moisture content. Litter beneath red trees contained large amounts of terpenes, including compounds known to increase foliage flammability that remain in the litter throughout the fire season. Total terpene content emitted from red foliage is greater than green-infested or yellow foliage.

<p>A large portion of the anthropogenic emissions of greenhouse gases (<italic>GHG</italic>s) are cycled through the terrestrial biosphere. Quantifying the exchange of these gases between the terrestrial biosphere and the atmosphere is critical to constraining their atmospheric budgets now and in the future. These fluxes are governed by biophysical processes like photosynthesis, transpiration, and microbial respiratory processes which are driven by factors like meteorology, disturbance regimes, and long term climate and land cover change. These complex processes occur over a broad range of temporal (seconds to decades) and spatial (millimeters to kilometers) scales, necessitating the application of simplifying models to forecast fluxes at the scales required by climate mitigation and adaptation policymakers. </p><p>Over the long history of biophysical research, much progress has been made towards developing appropriate models for the biosphere-atmosphere exchange of <italic>GHG</italic>s. Many processes are well represented in model frameworks, particularly at the leaf scale. However, some processes remain poorly understood, and models do not perform robustly over coarse spatial scales and long time frames. Indeed, model uncertainty is a major contributor to difficulties in constraining the atmospheric budgets of greenhouse gases. </p><p>The central objective of this dissertation is to reduce uncertainty in the quantification and forecasting of the biosphere-atmosphere exchange of greenhouse gases by addressing a diverse array of research questions through a combination of five unique field experiments and modeling exercises. In this first chapter, nocturnal evapotranspiration -- a physiological process which had been largely ignored until recent years -- is quantified and modeled in three unique ecosystems co-located in central North Carolina, U.S.A. In the second chapter, more long-term drivers of evapotranspiration are explored by developing and testing theoretical relationships between plant water use and hydraulic architecture that may be readily incorporated into terrestrial ecosystem models. The third chapter builds on this work by linking key parameters of carbon assimilation models to structural and climatic indices that are well-specified over much of the land surface in an effort to improve model parameterization schemes. The fourth chapter directly addresses questions about the interaction between physiological carbon cycling and disturbance regimes in current and future climates, which are generally poorly represented in terrestrial ecosystem models. And the last chapter explores effluxes of methane and nitrous oxide (which are historically understudied) in addition to CO₂ exchange in a large temperate wetland ecosystem (which is an historically understudied biome). While these five case studies are somewhat distinct investigations, they all: a) are all grounded in the principles of biophysics, b) rely on similar measurement and mathematical modeling techniques, and c) are conducted under the governing objective of reducing measurement and model uncertainty in the biosphere-atmosphere exchange of greenhouse gases.</p> / Dissertation

Thesis (M.S.)--Oregon State University, 2003. / Typescript (photocopy). Includes bibliographical references (leaves 85-92). Also available online.

The pine beetle is transforming BC's lush greenery into a sea of red death. Jorg Bohlmann looks to the conifer tree for clues on how to halt the beetle's rampant spread.

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