Browsing by Author "Marcia Gumpertz, Committee Member"

Now showing 1 - 5 of 5

Caution Using Bootstrap Tolerance Limits with Application to Dissolution Specification Limits
(2007-11-22) Bergquist, Mandy; Marcia Gumpertz, Committee Member; Daowen Zhang, Committee Member; Dennis Boos, Committee Member; Marie Davidian, Committee Chair
Large-scale analysis of sustainable forest management indicators: assessments of air pollution, forest disturbance, and biodiversity
(2004-06-28) Coulston, John Wesley; William D Smith, Committee Member; Kurt Riitters, Committee Member; Heather Cheshire, Committee Chair; Marcia Gumpertz, Committee Member
As the doubling time of the global human population decreases, increasing emphasis is placed on sustainable development by both policy makers and scientists. Sustainable forest management is one part of the overall picture of sustainable development. One method to assess sustainable forest management is through the use of criteria and indicators. Criteria represent sustainable management goals. Indicators are measurable quantities that designate whether the goals are being met. The maintenance of forest health and vitality is a criterion of the Montrêal Process Criteria and Indicators for the Conservation and Sustainable Management of Temperate and Boreal Forests. Measures of air pollution, forest disturbance, and change in ecological integrity provide indicators of how well forest health and vitality are being maintained. Using national databases, I assess air pollution in the United States, demonstrate the use of epidemiological approaches to examine forest disturbances, and develop an analytical technique to identify gaps and target priorities in reserve networks. The analyses in this dissertation offer new approaches to large-scale analysis of Montrêl Process Criteria and Indicators. The results can be summarized as follows. (1) From 1994 through 2000 air pollution was highest in the northeastern United States and the oak-hickory and loblolly-shortleaf forest type groups were consistently exposed to more air pollution than other forest types. Conversely, the western white pine and larch forest type groups were consistently exposed to less air pollution than all other forest types. (2) Examination of the southeastern United States revealed high rates of forest fragmentation in the piedmont and coastal plain region. In the Pacific North west, insect and pathogen activity was analyzed and recurring clusters of high rates of activity were identified. (3) Although protected areas of the Douglas-fir forest type group occurred throughout much of the species range, most existed in colder and drier parts of the range. To conserve representative habitats, future conservation efforts would be most effective in warmer and wetter areas of western Oregon, northwestern Washington, and northwestern California.
Rapid Screening for Solid Wood Quality Traits in Clones of Loblolly Pine (Pinus Taeda L.) by Indirect Measurements
(2008-03-06) Eckard, Jonathan Tyler; Bailian Li, Committee Member; Marcia Gumpertz, Committee Member; Bronson Bullock, Committee Co-Chair; Fikret Isik, Committee Co-Chair
Clonal forest has the potential to greatly improve the quality and uniformity of wood derived from pine plantations. However, conventional field sampling and laboratory analysis of wood samples are prohibitively time consuming and expensive to facilitate the necessary mass screening of wood quality in clones. New methods need to be assessed for providing indirect non-destructive measurements of wood quality that can be rapidly and reliably utilized in young clonal tests. This study assessed a drill resistance tool called the Resistograph and a time-of-flight acoustic tool called the TreeSonic for their efficiency at screening young clones of loblolly pine for three economically important solid wood properties: wood density, modulus of elasticity (MOE), and modulus of rupture (MOR). A single clonal trail containing clones from three elite full-sib families of loblolly pine was used to assess the efficiency of indirect selection. Increment cores and static bending samples were collected along with growth measurements from the clones at age 8. Basic wood density was measured at breast height and for the whole-tree using x-ray densitometry on the increment cores, as well as volume and weight measurements on clear wood bending samples. MOE and MOR were determined from static bending tests on clear wood samples. Clone means for wood properties were moderately to highly repeatable and intense clonal selection resulted in genetic gains over the site mean ranging from 11.1 % for wood density to19.9 % for MOE. After this adjustment for effects of friction, clone means for Resistograph amplitude values had moderately strong correlations with wood density at both breast-height (0.75) and for the entire stem (0.72). Genetic correlations between amplitude and density were quite strong, with estimates ranging between 0.92 and 1.00. Amplitude was weakly correlated with MOE and MOR at the phenotypic level but were moderately related at the genetic level. Clonal variation explained only 20 % of the phenotypic variance for amplitude, such that disparities between the genetic and phenotypic correlations were due to the low repeatability of clone means for amplitude. The efficiency of the Resistograph was high for screening clones for wood density, moderate for MOR, and rather poor for MOE. TreeSonic stress wave speed measurements (SWS) were highly repeatable and had moderate and highly significant clone mean correlations with mechanical wood properties. SWS was largely uncorrelated with wood density. Thus, SWS was highly efficient at selecting clones for MOE, moderate for MOR, and poor for density; reverse of the results for amplitude. SWS and amplitude were unrelated and provided independent information regarding the variation in mechanical wood properties, such that combining them into a single index for selection increased selection efficiencies. Simultaneous gain for growth and solid wood quality could be achieved using clonal selection indices based on indirect wood quality measurements. Substantial gain for both growth and wood quality required that moderate proportional economic weights be used. Simultaneous selection was complicated by negative genetic correlations between MOE and growth traits, as well as by relatively low variation among clone means for MOR and density compared to volume. Obtaining considerable gains for wood traits resulted in large reductions from optimal volume gains, and justifying such losses for volume gain in deployment populations may be difficult. It appears that drill resistance and acoustic methodologies are currently developed to the extent that they can be reliably applied for screening and selecting clones for wood quality. These methods were shown to be rapid, inexpensive, and effective at providing desirable genetic gains. Reliability and selection efficiencies are expected to improve, especially for the Resistograph, as the sources contributing to extraneous environmental error in the measurements are identified and corrected.
Seasonal Nutrient Dynamics and Vertical Nutrient Distribution in Loblolly Pine (Pinus taeda)
(2002-08-19) Winborne, Ian Christopher; Marcia Gumpertz, Committee Member; Barry Goldfarb, Committee Member; H. Lee Allen, Committee Member
Nutrient deficient stands may respond favorably to nutrient additions. However, deficient stands must be efficiently identified. Leaf area has been shown to diagnose gross nutrient deficiencies while chemical analysis of foliage can provide more specific nutritional data. Nutrient levels fluctuate throughout the year and vary with crown position. Therefore, it is important to know the proper time and location for foliage sampling. The effects of nutritional treatments and time on foliar nutrient status were studied at SETRES. SETRES is a 2X2 factorial study of optimum nutrition and water additions in Scotland County, North Carolina, USA. Monthly foliage samples were collected and nutrient concentration and contents were determined for each sample for examination of seasonal variation. Foliage samples were collected in 1994, 1996, and 1998 and nutrient concentration and contents were determined for each sample for examination of vertical distribution patterns. Fertilization significantly increased the nutrient content of all nutrients added. Copper concentrations increased on fertilized plots even though no Cu was added. Fertilization caused changes in seasonal nutrient dynamics of added nutrients, especially B. Retranslocation efficiencies of N, P, and K decreased with fertilization while retranslocation rates of several micronutrients increased. Concentrations of mobile nutrients increased with crown height while concentrations of immobile nutrients decreased with crown height. Distribution patterns also changed with fertilization. For example, boron concentrations on fertilized plots increased with crown height while concentrations on control plots decreased with crown height. The ability to detect differences among sites and stability in concentrations are two criteria used to develop appropriate sampling protocols. Greatest sensitivity to detect site difference may occur at the times of year when the largest treatment differences occurred in this study. Unfortunately, concentrations are highly dynamic during those periods making the sampling window so small that it is impractical to use these periods for operational sampling. We recommend that foliage be sampled during the dormant season when nutrient concentrations are stable and there appears to be reasonable opportunity to detect difference among sites as indicated by significant treatment differences in this study. Greatest sensitivity to detect site difference may occur in the upper crown, where the largest treatment differences occurred in this study. Therefore we recommend that foliage be sampled from upper crown positions.
Testing for Unit Roots in Seasonal Time Series with Long Period.
(2009-03-15) Zhang, Ying; Marcia Gumpertz, Committee Member; Peter Bloomfield, Committee Member; David Dickey, Committee Chair; Sastry Pantula, Committee Member
Testing for seasonal unit roots has been discussed extensively in the literature. However, the test will be difficult if the time series has a long period, where the critical values for the test statistics are not available. We modify the seasonal unit roots test of Dickey, Hasza, and Fuller (1984) to investigate results for less typical, long period cases, and present some asymptotic normality properties. We also suggest an empirical adjustment to improve the normal approximation when the seasonal period is not sufficiently long. The basic idea is to use a double-index form for the seasonal time series with a long period, where d denotes the large lag number, so that the d "channels" will be independent for each i. By applying the Classical Central Limit Theorem for iid random variables, we can obtain the asymptotic result. The convergence is proved to be order independent with respect to m and d. An advantage of this technique is that one can make the adjustment and use a standard normal as a reference distribution instead of looking into the seasonal percentile tables when doing the seasonal unit roots test, no matter what kind of deterministic terms are included in the model as long as the number of the regressors is fixed. We also show that for an AR(p) model we still obtain the asymptotic normality of the unit root statistics.