M. S.

SPBMODEL, a legacy southern pine beetle (SPB) simulation model, was translated into a new JavaTM model called Javahog. The Javahog output was verified to be essentially identical to SPBMODEL output by means of standard and paired t-tests. Javahog was placed online and is currently accessible via a servlet. Genetic algorithms (GAs) were applied to the Javahog model. GAs are a type of optimization heuristic that operate as an analog to evolution. GAs "evolve" a very good solution to a complex problem. In this case, GAs were intended to evolve a very good version of SPBMODEL. GAs were applied in part to improve upon the SPBMODEL design, and in part to demonstrate that GAs are effective tools for recalibrating legacy simulation models. Beyond simply recalibrating model parameters, the GA was used to select optimal functional forms for the development rates of each SPB life stage. The GA evolved a model that performed better than SPBMODEL at predicting observed field data, according to a balanced fitness function and according to sums of squared errors. However, from a visual comparison of the output of both models versus observed field data, neither model achieved satisfactory performance. / Master of Science

The southern pine beetle (SPB) (Dendroctonus frontalis Zimm.) is one of the most destructive forest insect pests in the southeastern United States and has historically had a large impact on the forests of North Carolina. Many characteristics of a forest can contribute to SPB susceptibility including stand density, growth rate, age, soil type, and position on the landscape. This work was undertaken in an effort to assist and improve on the current federal SPB hazard modeling being conducted for North Carolina by the USDA Forest Service – Forest Health Protection's Forest Health Technology Enterprise Team (FHTET). In our study, predictive SPB susceptibility models were developed for each physiographic region in North Carolina using two variables not currently included in the FHTET modeling, mean stand age and the in-stand percentage of sawtimber-sized pines. These variables were obtained from USDA Forest Service – Forest Inventory and Analysis (FIA) data and North Carolina Forest Service historical SPB records creating a dataset of both infested and non-infested stands and the models were developed using the CART® classification tree approach. Two model-derived age classes (older than and younger than 22 years) were identified on the landscape using current Landsat 5 Thematic Mapper (TM) imagery chronosequences of disturbance index (DI) â transformed scenes to identify stand-replacing disturbances, resulting in a kappa statistic of 0.6364 for the younger than 22 year age class and 0.7778 for the older than 22 years age class. A kappa value of 1 is ideal. The CART® modeling effort produced valid models in all three physiographic regions of North Carolina, though the complexity of the piedmont model makes it impractical for use in the field. The dependent variable in the classification tree was presence or absence of SPB outbreak and the test sample error percentages were similar across regions, with errors ranging between 23.76 - 34.95 percent. Overall prediction success, based on the software's internal cross-validation procedure, was likewise comparable across the regions with 72.28 - 89.56 percent correctly predicted. Based on our modeling, stand age and percent sawtimber should be included in future FHTET SPB hazard modeling efforts for the coastal plain and mountains, respectively. Age classes can be reasonably estimated using Landsat or other multispectral imagery. / Master of Science

Thesis (Ph. D.)--University of Washington, 2006. / Vita. Includes bibliographical references (leaves 89-98).

Master of Science

Today, climate change and rapid ecological change are impacting our ecosystems and landscapes in numerous, often surprising ways. These changes result in social, cultural, ecological, and economic shifts, as exemplified in the climate-exacerbated mountain pine beetle (MPB) outbreak in British Columbia. Recently, scientific communities have boosted calls for “usable science.” By interviewing leading MPB scientists, I ask, “How are scientists and their institutions responding to rapid ecological change?” Numerous factors shape MPB science—institutional support, funding, and values—and these factors enable and constrain effective relationships and ultimately, useful science, in response to the outbreak. Results suggest that while science and scientific institutions change slowly, and while relationships between MPB science and policy are characterized as tenuous, there are signs that crossing institutional boundaries (such as the TRIA Network) contributes to producing science that is more effective for responding to rapid ecological change. / Graduate

Typescript (photocopy). / Digitized by Kansas Correctional Industries

Lodgepole pines Pinus contorta (Douglas) were treated by girdling to assess the response by an endemic population of mountain pine beetle Dendroctonus ponderosae (Hopkins) (Coleoptera: Scolytidae). Capture in 'sticky traps' indicated that the beetles were attracted while in flight towards the wounded trees. A significant difference in the landing rates of bark beetles between the treated and untreated trees indicated that the beetles were able to distinguish wounded from non-wounded trees while still in flight. Pressure chamber readings demonstrated that water stress developed in the girded trees when compared to the non-girdled trees.

The mountain pine beetle is associated with a diverse array of fungi. Grosmannia clavigera is the most pathogenic of these fungi. A comparison was made between two methods that have been used to assess fungal pathogenicity. Results were similar for older trees inoculated with G. clavigera using either the alternating flap technique or cork borer method. Using the cork borer method, younger lodgepole pine trees were inoculated with five different isolates of G. clavigera. After a 48 week incubation period, isolates ATCC 18086, B5 and H55 had induced stronger pathogenic indicators compared to isolates KW 1407 and B20. After a 7 week incubation period, only isolate ATCC 18086 had induced stronger pathogenic indicators. Usually, this isolate grew faster at lower temperatures and in a low oxygen environment. Isolate KW 1407 consistently produced milder pathogenic indicators during both incubation periods. Among the non-pathogenic fungal associates of the mountain pine beetle, Ceratocystiopsis minuta may be considered the most important because it is the type species for the genus Ceratocystiopsis. The history of this genus is complicated because no physical specimen exists for C. minuta. The phylogeny of the genus Ceratocystiopsis was evaluated. Many isolates of C. minuta were assessed as potential epitypes. Several isolates of C. minuta from previous work were shown to be misidentified. C. minuta isolate CBS 116796 is recommended for future genetic work within the genus Ceratocystiopsis. For morphological work, using measurements from the literature is recommended since CBS 116796 did not produce fruiting bodies.

A method of linking SORTIE-ND and PrognosisBC was developed for the purpose of predicting natural regeneration and forecasting future stand conditions in mountain pine beetle (Dendroctonus ponderosae Hopkins - MPB) attacked stands in the Interior Douglas-fir (IDF) and Sub-Boreal Spruce (SBS) biogeoclimatic ecosystem zones of central and southeastern British Columbia. PrognosisBC, a spatially-implicit growth model, lacked a submodel suitable for predicting natural regeneration in unsalvaged MPB-disturbed stands. To fill this gap, estimates of regeneration (trees <7.5 cm diameter at breast height - DBH) were supplied to PrognosisBC using the light-mediated forest dynamics model SORTIE-ND and the linked model was used to forecast future stand conditions. In order to improve results, a density-dependent system of crown allometry equations to predict crown depth and crown radius was developed and then added to SORTIE-ND. The equations used stand-level measures of stems ha-¹, basal area (m² ha-¹), and the basal area of trees taller than the target tree to explicitly account of the effects of crowding on the crown axes. Additionally, crown radius and crown depth were used as dependent regressors. The equations were fit using a nonlinear three-stage least squares estimator and generally provided good estimates of crown depth and crown radius for lodgepole pine (Pinus contorta var. latifolia), hybrid spruce (Picea engelmannii x glauca (Moench) Voss), Douglas-fir (Pseudotsuga menziesii var. glauca (Beissn.) Franco) and trembling aspen (Populus tremuloides Michx.). Tests of the hybrid model with the improved system of crown allometry equations were performed using reconstructed plot data collected from natural stands disturbed by MPB 25-years ago. The hybrid model provided good estimates (small mean bias and low root mean square error) for the basal area of advance regeneration (2 < DBH < 7.5 cm) for lodgepole pine (Pinus contorta var. latifolia). The best estimates were achieved when trees <7.5 cm DBH were transferred from SORTIE-ND to PrognosisBC 15-years after MPB-disturbance. For trees <2 m in height, poor estimates of stems ha-¹ where obtained. Despite the shortcomings with respect to trees <2 m tall, the results suggest that linking SORTIE-ND and PrognosisBC is an effective method of building a hybrid model capable of being used in MPB-disturbed forests. However, full parameterization of the SORTIE-ND model is likely needed to obtain accurate estimates for all sizes of natural regeneration.