The study dealt with developing methodologies for predicting basal area distributions and individual tree basal areas. Data for the study was from the Hill Farm Experiment Station at Homer, Louisiana. Five height-diameter (basal area) curves were examined to determine which was most appropriate for the data set utilized. The model H = a + b log(BA), where H denotes height and BA denotes basal area, was chosen as best, based on several fit and prediction oriented statistics. A stochastic basal area distribution model, called the parameter distribution model, was developed. The model was based on the Chapman-Richards growth curve. This curve was fit to all stems on approximately 3/4 of the data set. Two parameters of the curve were fixed a priori, leaving two parameters to be estimated. A sampling distribution was fit to the estimates of the rate parameter, k. Models were developed to predict the parameters of this distribution from stand variables. A model was then derived to predict m, the shape parameter of the C-R curve, from k and stand variables. Finally, an existing survival function was modified. The overall model was implemented as follows: first, the number of surviving stems was predicted. Then k and m values were predicted for each predicted stem. Substitution of these two values into the C-R curve yielded a predicted basal area for each stem. The previously mentioned height diameter curve was employed to predict a height for each predicted basal area. Stochastic elements were built into the prediction model for m and the height-diameter curve. Predicted basal area and height distributions were compared to observed on the remaining 1/4 of the data set. Although the two--sample K-S test was statistically significant, the observed and predicted distributions did appear to be close, in general, from a practical standpoint. This approach appears promising as a stochastic method of predicting size distributions. The Chapman-Richards curve was also modified for use as an individual tree basal area growth model. Two parameters of the curve were fixed, and the remaining two were modelled as functions of tree- and stand-level variables. The modified growth function fit the data well, but on an independent data set, a simpler linear model of basal area growth performed better in terms of mean difference and mean absolute difference between observed and predicted basal areas. Thus, the only anticipated use of the modified C-R model is in situations where extrapolation beyond the range of observed data is required, since this model has desirable long-term characteristics, whereas the linear model does not. / Ph. D.

An integrated system of stand models was developed for loblolly pine in which models of different levels of resolution are related by a unified mathematical structure. A “telescoping'' system is presented in which a highly detailed overall model is specified and its components. ''collapsed" around a common set of growth and survival functions to provide structurally compatible models at each successively lower stage of resolution. The most detailed model is a distance dependent individual tree model which simulates the growth and competitive interaction of trees in a stand. Tree basal area and height growth were modeled using a modified Chapman-Richards function in terms of potential growth, current size, relative size, crown ratio, and an index of competition. Potential growth was considered a function of site quality, age, and open-grown size relationships. Tree survival probability was described using a logistic function in terms of age, crown ratio, and competition. The competition or point density index is a function of the size and location of neighbors. Published indices were evaluated and compared on their simple correlation with growth, multiple correlation with growth in the presence of other tree and stand measures, computer execution time, and relationships to stand level density measures. The area potentially available (APA) for each tree was chosen as the most suitable. The APA index is calculated as the area of the polygon constructed from lines which divide the distance between a tree and its neighbors. Mean APA, or average area per tree, is estimated by the inverse of trees per unit area, permitting point density to collapse to stand density, resulting in a distance independent individual tree model. This model was collapsed dimensionally to consider trees grouped in size classes. Tree growth and survival equations are applied to the mean attributes of each size class, resulting in a size class projection model. At the lowest level of resolution, the dimensions of the model are collapsed to one "average" tree. A stand level projection model results from applying the tree growth and survival equations to the stand's average tree attributes. At the stand level, the basal area growth function provides a transformation which, for a number of probability density functions (pdf's), will regenerate the initial pdf family. Considering a normal pdf to describe basal area distributions, a pdf-based size distribution model is presented, in which the projected parameters are expressed in terms or the growth function coefficients. Applications to other pdf families are discussed. Preliminary tree growth and survival equation coefficients were estimated using data from a loblolly pine stand density study in North Louisiana. Structurally compatible models at each level of resolution are detailed. Considerations for numerically consistent estimates from models of different levels of resolution are discussed in terms of model specification, estimation, and implementation. Recommendations for model application and future model development are presented. / Ph. D.

Nitrogen is the most frequently limiting nutrient in southern pine plantations.  Previous studies found that only 10 to 25% of applied urea fertilizer N is taken up by trees.  Enhanced efficiency fertilizers could increase tree uptake efficiency by controlling the release of N and/or stabilize N.  Three enhanced efficiency fertilizers were selected as a representation of fertilizers that could be used in forestry: 1) NBPT treated urea (NBPT urea), 2) polymer coated urea (PC urea), and 3) monoammonium phosphate coated NBPT treated urea (MC NBPT urea). Urea, MC NBPT urea, and NBPT urea fertilizer treatments showed an extractable NH4+ spike 14 days after fertilization while the polymer coated urea showed a spike in NH4+ 49 days after fertilization. Total ecosystem recovery of fertilizer in each treatment was; MC NBPT urea, 51.29 g N; NBPT urea, 48.87 g N; urea, 45.09 g N; and PC urea, 31.30 g N which represents 78.7%, 74.7%, 72.1%, and 47.6% respectively of the total N applied.  For the MC NBPT urea, NBPT urea, and PC urea treatments the largest sinks for N were the forest floor and mineral soil.  The largest sink for fertilizer applied N in the urea treatment was in the tree.  The 2011 foliage cohort was the largest sinks for fertilizer N recovered by the tree.  N volatilization was around 20% for all fertilizer treatments except polymer coated fertilizer, which was 1.1%.  Urea preformed the same as the soluble enhanced efficiency fertilizers and better than the PC urea fertilizer.  The results emphasize the importance of climatic conditions on fertilizer release and effectiveness. / Master of Science

The use of nitrogenous fertilizers in agricultural and forestry practices coupled with increased fossil fuel combustion and resulting nitrogen (N) deposition across the landscape have contributed to a near doubling of N inputs to terrestrial ecosystems.  With such dramatic changes have come adverse environmental consequences including the acidification of soil and water resources and an increased rate of biodiversity loss in both flora and fauna.  A method of rapidly predicting ecosystem susceptibility to N loss across large spatial scales would facilitate the identification of those systems most likely to contribute to potentially adverse environmental impacts.  To begin the development of such a framework, this research utilizes study sites located throughout the geographic ranges of Douglas-fir (Pseudotsuga menziesii) and loblolly pine (Pinus taeda) to explore relationships between hyperspectral remote sensing, N stable isotope ratios ("15N) and growth response to nitrogenous fertilizer.  In both species multiple linear regression models relating leaf-level reflectance to "15N showed strong predictive capabilities, with some models explaining more than 65% of the variance in "15N.  Significant correlations between "15N metrics and growth response to N fertilization were also observed in both species.  Additional exploratory analysis of the inclusion of "15N metrics with other environmental and edaphic variables to predict fertilizer growth response showed an increase in model performance with the addition of the enrichment factor (EF ="15NFol - "15NSoil).  This research demonstrates the ability of hyperspectral reflectance to predict "15N and reveals the potential of "15N to be included in future models to predict fertilizer growth response. / Master of Science

The effect of date and method of lifting on ethylene production by 1-0 loblolly pine (Pinus taeda L.) seedlings during cold storage, the dose-response relationship between ethylene and loblolly pine seedlings during cold storage, and the effect of water stress on ethylene and aminocyclopropane-1-carboxylic acid (ACC) production in two half-sib loblolly families were investigated. Seedlings stored in Kraft-Polvethvlene (K-P) bags showed a general trend of increasing ethylene concentrations from November through February, with an abrupt drop in March. Production rates may be related to the level of dormancy of the seedlings, with the peak in production corresponding to fulfillment of the chilling requirement. Ethylene concentrations within the K-P bags generally declined over the twelve weeks in cold storage. Roots produced significantly higher levels of ethylene while stored in the K-P bags; however, when incubated under light, the needles produced higher concentrations. Roots of machine-lifted seedlings produced significantly higher levels of ethylene than roots of hand-lifted seedlings. However, rates tended to moderate during storage and differences in production between HL and ML whole seedlings were not significant, which suggests that mechanical lifting is not a source of increased ethylene production. A dose-response study indicated that ethylene fumigation during cold storage tended to slightly enhance growth of outplanted seedlings. The effects of water stress on a Virginia Coastal Plain (CP) and an East Texas Drought Hardy (DH) loblolly family were also investigated. Ethylene production during severe stress (-2.8 MPa) appeared to be related to drought hardiness, with the CP seedlings producing much higher levels. Roots of both families produced greater levels of ethylene than the needles and may be due to an enhanced ability to convert 1-Aminocyclopropane-1-carboxylic acid (ACC) to ethylene. / Master of Science

Remote sensing offers many advantages to previous forest measurements, such as limiting costs and time in the field. Light detection and ranging (lidar) has been shown to enable accurate estimates of forest height. Lidar does produce precise measurements for ground elevation and forest height, where and when it is available. However, it is expensive to collect and does not have wall-to-wall coverage in the United States. In this study, we estimated height using the National Agricultural Imagery Program (NAIP) photogrammetric point clouds to create a predicted height map for managed loblolly pine stands in the southeastern United States. Recent studies have investigated the ability of digital aerial photogrammetry (DAP), and more specifically NAIP, as an alternative to lidar as a means of estimating forest height due to its lower costs, frequency of acquisition, and wall-to-wall coverage across the United States. Field-collected canopy height for 534 plots in Virginia and North Carolina were regressed against the 90th percentile derived from NAIP point clouds. The model for predicted pine height using the 90th percentile of height (P90) is predicted pine height = 1.09(P90) – 0.43. The adjusted R^2 is 0.93, and the RMSE is 1.44 m. This model is being used to produce a 5 m x 5 m canopy height model for all pine stands across Virginia, North Carolina, and Tennessee. NAIP-derived point clouds are thus a viable means of predicting canopy height in southern pines. / M.S. / Collecting accurate measurements of pine plantations is essential to managing them to maximize various ecosystem goods and services. However, it can be difficult and time-consuming to collect these measurements by hand. This study demonstrates that point clouds derived from digital stereo aerial photograms enable calculating forest height to an accuracy sufficient for pine plantation management. We developed a simple linear regression model to predict forest canopy height using the 90th percentile of the photo-derived heights above the ground in a given area. With this model, we created a map of pine plantation canopy heights (consisting of 5 m x 5 m grid cells, each containing a canopy height estimate) for pine forests in Virginia, North Carolina, and Tennessee. Digital aerial photography from the National Agricultural Imagery Program (NAIP) is repeated every three years for a given state, allowing growth to be mapped over time. Photography collected by NAIP and similar programs also has uniform acquisition parameters in a given year applicable over large regions. State- and national photography programs like NAIP are also less expensive than other data sets, like airborne laser scanning data, that enable estimation of tree height.

Informed forest management requires accurate, up-to-date information. Ground-based forest inventory is commonly conducted to generate estimates of forest characteristics with a predetermined level of statistical confidence. As the importance of monitoring forest resources has increased, budgetary and logistical constraints often limit the resources needed for precise estimates. In this research, the incorporation of ancillary information in planted loblolly pine (Pinus taeda L.) forest inventory was investigated. Additionally, a simulation study using synthetic populations provided the basis for investigating the effects of plot and stand-level inventory aggregations on predictions and projections of future forest conditions. Forest regeneration surveys are important for assessing conditions immediately after plantation establishment. An unmanned aircraft system was evaluated for its ability to capture imagery that could be used to automate seedling counting using two computer vision approaches. The imagery was found to be unreliable for consistent detection in the conditions evaluated. Following establishment, conditions are assessed throughout the lifespan of forest plantations. Using small area estimation (SAE) methods, the incorporation of light detection and ranging (lidar) and thinning status improved the precision of inventory estimates compared with ground data alone. Further investigation found that reduced density lidar point clouds and lower resolution elevation models could be used to generate estimates with similar increases in precision. Individual tree detection estimates of stand density were found to provide minimal improvements in estimation precision when incorporated into the SAE models. Plot and stand level inventory aggregations were found to provide similar estimates of future conditions in simulated stands without high levels of spatial heterogeneity. Significant differences were noted when spatial heterogeneity was high. Model form was found to have a more significant effect on the observed differences than plot size or thinning status. The results of this research are of interest to forest managers who regularly conduct forest inventories and generate estimates of future stand conditions. The incorporation of auxiliary data in mid-rotation stands using SAE techniques improved estimate precision in most cases. Further, guidance on strategies for using this information for predicting future conditions is provided. / Doctor of Philosophy / Informed forest management requires accurate, up-to-date information. Groundbased sampling (inventory) is commonly used to generate estimates of forest characteristics such as total wood volume, stem density per unit area, heights, and regeneration survival. As the importance of assessing forest resources has increased, resources are often not available to conduct proper assessments. In this research, the incorporation of ancillary information in planted loblolly pine (Pinus taeda L.) forest inventory was investigated. Additionally, a simulation study investigated the effects of two forest inventory data aggregation methods on predictions and projections of future forest conditions. Forest regeneration surveys are important for assessing conditions immediately after tree planting. An unmanned aircraft system was evaluated for its ability to capture imagery that could be used to automate seedling counting. The imagery was found to be unreliable for use in accurately detecting seedlings in the conditions evaluated. Following establishment, forest conditions are assessed at additional points in forest development. Using a class of statistical estimators known as small-area estimation, a combination of ground and light detection and ranging data generated more confident estimates of forest conditions. Further investigation found that more coarse ancillary information can be used with similar confidence in the conditions evaluated. Forest inventory data are used to generate estimates of future conditions needed for management decisions. The final component of this research found that there are significant differences between two inventory data aggregation strategies when forest conditions are highly spatially variable. The results of this research are of interest to forest managers who regularly assess forest resources with inventories and models. The incorporation of ancillary information has potential to enhance forest resource assessments. Further, managers have guidance on strategies for using this information for estimating future conditions.

The controversy regarding commercial thinning continues to intensify as pine plantation acreage in the south increases. This controversy has caused industrial and nonindustrial landowners to re-examine the economic returns from their plantation investments. This study was undertaken to develop investment guidelines for the management of loblolly pine plantations. Computer simulation was used to evaluate the effect on present value that four future price/market scenarios, three management regimes, and three mechanized thinning systems can have on current thinning investments. When the economic returns from thinning are compared with a no-thin management regime, simulation results indicate that long-term investment advantages favor thinning only slightly, regardless of the future price/market scenario assumed. This slight difference suggests that individual forest product companies may find other reasons such as wood flow, tax advantages, and future product requirements of their manufacturing facilities to be overriding factors for engaging in commercial thinning. Generally, short-run cost and production differences between thinning systems are more significant than the long-term investment effects. Consequently, the type of mechanized thinning system employed has a negligible impact on the total investment. / Ph. D.

Heat shock proteins (HSPs) are expressed in response to environmental stresses. Compared to other kingdoms, plant HSP families are larger, presumably the result of adaptation to a wide range of stresses. Following on an analysis of drought stress characteristics in loblolly pine (Watkinson et al., 2003), expression patterns of HSP gene expression during photosynthetic acclimation were examined. One cycle of mild (-1Mpa) followed by two cycles of severe stress (-1.7Mpa) were probed for conditioning effects. Photosynthetic acclimation occurred after the first cycle. No acclimation occurred without the first mild cycle. Microarray/RT-PCR analyses showed that a pine homolog to GRP94 (ER-resident HSP90) was up-regulated after rehydration coincident with acclimation. This GRP94 is closely related to GRP94 from the desiccation tolerant plant X. viscosa, supporting the importance of this gene during acclimation to water deficit. HSP genes whose products localized to the mitochondrion showed gradual up-regulation after consecutive cycles of severe drought. The Arabidopsis pine GRP94 homolog, (AtHSP90-7) was then analyzed, using bioinformatics (Pati et al., 2006) and laboratory tools. Genes encoding putative candidate co-chaperones for GRP94 and other HSP90s were discovered, which contained water stress-related cis-elements. Arabidopsis (Col-0) wild type and two T-DNA insertion mutants in HSP90-7 were used to study the importance of this gene for photosynthetic acclimation. Only the mutants were able to acclimate to drought stress, with the level of AtHSP90-7 expression in the mutants being reduced compared to the wild type. AtHSP90-7 may have a different role in Arabidopsis, and its reduced expression activated other protective genes (Klein et al., 2006). Responses to extreme drought in resistant (Sullu) and susceptible (Negra Ojosa) lines of Andean potatoes were also compared in order to identify relationships between HSPs gene expression, and tolerance, defined as the ability to maintain photosynthesis at 50% after 25 days of drought and to recover from the stress. Tolerance was correlated with up-regulation of HSPs (mostly chaperonins) and antioxidant genes all of whose gene products are located in the chloroplast. / Ph. D.

The Lower Coastal Plain of the southeastern United States is a major wood producing region. The region is characterized by a combination of nearly-level topography, poorly-drained soils, and high rainfall, which results in a perched water table in some soils that inundates the surface several times each year. Harvesting timber under wet site conditions often results in extensive soil compaction, rutting, soil displacement, and waterlogging. Forest managers are concerned that these visually-displeasing soil disturbances may cause site damage and reduced productivity. These concerns were addressed in an operational-scale field experiment conducted in South Carolina. The objectives of this experiment were to determine: (i) if soil disturbance changes key soil properties and processes; (ii) if soil disturbance reduces loblolly pine productivity; and, (iii) if disturbance can be mitigated with site preparation practices? Three 20-ha, 20-yr-old loblolly pine (Pinus taeda L.) plantations were harvested under wet and dry conditions to create a broad gradient in soil disturbance. Within each harvested plantation, a subset of 3-ha plots were site prepared by either bedding, or mole-plowing plus bedding, then all sites were established as 3rd -rotation pine plantations. Prior to site preparation, each plot was classified and mapped using a 5 by 5 soil disturbance (none to churned) by organic debris (none to slash piles) classification matrix. Within each plot, data were collected on several soil physical, chemical, and biological properties over a 2-yr period following site preparation. Key soil properties were integrated into a Soil Quality Index (SQI) and compared to aboveground productivity of 2-yr-old loblolly pine trees growing on closely-spaced (30 by 30 cm) bioassay plots planted across the gradient of soil disturbance. The soil physical properties were used to determine the least limiting water range (LLWR), the range in soil water content within which root growth is not limited. Soil compaction and deep rutting reduced the LLWR. Retention of logging slash improved the LLWR for compacted and rutted soils. Site preparation improved the quality of the soil physical environment across all levels of soil disturbance. Soil disturbance had no effect on soil chemical or biological properties as evidenced by no change in soil pH, ECEC, base saturation, available P, or net N mineralization with disturbance. The base saturation exceeded 80 % on all sites, with Ca saturation controlling soil pH. The high base saturation buffered any redox-induced changes in soil chemistry that would have resulted from disturbance. The results showed that high fertility is an important mechanism for buffering the potentially-negative effects of soil disturbance on the soil nutritional environment. Site preparation changed soil chemical properties, but the changes were probably associated with tillage effects on organic matter and clay content, not redox processes. The SQI showed that surface soil compaction and deep rutting reduced soil quality, mainly by decreasing the LLWR and aeration depth. Site preparation mitigated the effects of most disturbances on soil quality, evidenced by similar aboveground biomass production among soil disturbance classes after bedding. A regression model was developed for predicting aboveground biomass production as a function of SQI. SQI explained 73 % of the variation in aboveground biomass production. The regression model showed that compression tracks and rutting decreased aboveground biomass production compared to undisturbed soils. The long-term effect of these disturbances on productivity will depend on natural soil recovery processes. However, these early results suggest that compaction and rutting should be minimized on similar sites, especially if sites will not be bedded before reforestation. The mole-plow / bedding treatment increased aboveground biomass production, indicating that this experimental treatment may be a viable practice for enhancing productivity. / Ph. D.