VTechWorks Repository :: Browsing by Author "Radtke, Philip J."

Browsing by Author "Radtke, Philip J."

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Applications of ecological modeling in managing Central Appalachian upland oak stands for old-growth characteristics
Grinter, Lawton E. (Virginia Tech, 2002-08-06)
Old-growth forests provide important habitat for wildlife, support the maintenance of biodiversity and serve as control areas for scientific research. Expanding current old-growth stand area by utilizing neighboring younger, managed stands allows private landowners to meet management needs and enables government agencies and private conservation organizations to meet old-growth forest objectives. Seven old-growth upland oak stands and seven adjacent younger, managed stands of the same site and stand type were measured in the Ridge and Valley, Blue Ridge, and Piedmont provinces of Virginia and Pennsylvania in an effort to characterize species composition, diameter distribution and canopy structure. A computer-based ecosystem/gap model (JABOWA-3) was modified and used to simulate silvicultural manipulations in the younger stands that would reproduce older forest characteristics. Various silvicultural techniques were used to convert the primarily even-aged younger stands into uneven-aged stands and then into old-growth. These manipulations included single-tree selection, herbicide application, culling larger diameter stems and planting seedlings where required. Individual trees within each of the younger, managed stands were removed at various time intervals and these simulated stands were then projected to a point in time in which the stand approximated the diameter distribution and composition of its paired old-growth stand. Several projections were made in each of the younger stands to meet this objective. Once a satisfactory projection was made for conversion of a younger stand to old-growth, a success rate was determined to gauge how close the simulated stand approximated the diameter distribution and composition of its old-growth counterpart. From this information, biologically feasible and environmentally sound management plans were created to carry out the silvicultural manipulations required by the model for each of the sites.
Applications of Imaging Spectroscopy in Forest Ecosystems at Multiple Scales
Stein, Beth R. (Virginia Tech, 2015-10-19)
Forests provide a number of ecosystem services which sustain and enrich the wildlife, human societies, and the environment. However, many disturbances threaten forest ecosystems, making it necessary to monitor their health for optimal management and conservation. Although there are many indicators of forest health, changes in biogeochemical cycling, loss of species diversity, and invasive plants are particularly useful due to their vulnerability to the effects of climate change and intensive agricultural land use. Thus, this work evaluates the use of imaging spectroscopy to monitor forest nutrient status, species diversity, and plant invasions in the Mid-Atlantic region. The research is divided into four separate studies, each of which evaluated a unique application for imaging spectroscopy data at a different scale within the forest. The first two studies examined loblolly pine nutrient status at the leaf and canopy scales, respectively. The first study determined that loblolly pine foliar macronutrient concentrations can be successfully modeled across the Southeastern US (R2=0.39-0.74). Following on these results, the second study focused on the relationship between physical characteristics, reflectance, and nutrients. Reflectance values and W scattering coefficients produced successful nitrogen models across loblolly pine plots at the canopy scale. Regression models showed similar explanatory power for nitrogen, although W scattering coefficients were significantly correlated with nitrogen at multiple wavelengths and reflectance variables were not. However, the direction of some of the correlations with W and the unusually high directional area scattering factor values indicate a need for further experimentation. The third study found that several imaging spectroscopy algorithms were moderately successful in identifying wavyleaf basketgrass invasions in mixed deciduous forests (overall accuracy=0.35-0.78; kappa=0.41-0.53). Lastly, the fourth study used a novel imaging spectroscopy/lidar fusion to identify canopy gaps and measure species diversity of understory vegetation. The lidar algorithm identified 29 of 34 canopy gaps, and regression models explained 49 percent of the variance in gap species diversity. In conclusion, imaging spectroscopy can be used to evaluate ecosystem health through forest nutrient status, nitrogen models, species diversity estimates, and identification of invasive plant species.
ArcGIS Pro, Python, and R-Bridge Support Small Area Estimation for Forests
Bell, David M.; Blinn, Christine E.; Peery, Stephen S.; Wynne, Randolph H.; Radtke, Philip J.; Thomas, Valerie A.; Oswalt, Christopher M.; Wilson, B. Ty (2023-07-12)
Auxiliary information resolution effects on small area estimation in plantation forest inventory
Green, P. Corey; Burkhart, Harold E.; Coulston, John W.; Radtke, Philip J.; Thomas, Valerie A. (2020-10)
In forest inventory, traditional ground-based resource assessments are often expensive and time-consuming forcing managers to reduce sample sizes to meet budgetary and logistical constraints. Small area estimation (SAE) is a class of statistical estimators that uses a combination of traditional survey data and linearly related auxiliary information to improve estimate precision. These techniques have been shown to improve the precision of stand-level inventory estimates in loblolly pine plantations using lidar height percentiles and thinning status as covariates. In this study, the effects of reduced lidar point-cloud densities and lower digital elevation model (DEM) spatial resolutions were investigated for total planted volume estimates using area-level SAE models. In the managed Piedmont pine plantation conditions evaluated, lower lidar point-cloud densities and DEM spatial resolutions were found to have minimal effects on estimates and precision. The results of this study are promising to those interested in incorporating SAE methods into forest inventory programs.
Basal Area Growth and Crown Dynamics in a Loblolly Pine Spacing Trial
Radtke, Philip J. (Virginia Tech, 1996-08-02)
Relationships between the culmination of basal area growth and degree of crown closure in loblolly pine (Pinus taeda L.) were investigated. A spacing trial established on the low Appalachian Piedmont and Atlantic Coastal Plain provided the data for the investigation. Test plots were planted at densities ranging from 303 to 2723 stems per acre, and at various rectangular and square spacings. Annual stem and crown measurements were used to derive the sought-after relationships. The age of basal area culmination was found to be inversely related to both planting density and site index. Crown closure was advanced on sites of relatively high quality, exhibiting an approximately linear increase with time from planting until the age of basal area culmination. The slope of this trend increased with planting density. The degree of crown closure at the age of basal area culmination was significantly higher on narrowly-spaced plots than it was on widely-spaced plots; however, it did not vary significantly with site index. Although crown closure is generally accelerated on high quality sites, the relatively early culmination of basal area growth on such sites offsets the increase - the net result being that crown closure at culmination age does not vary significantly with site differences. Crown closure indices can be used to determine whether or not a stand has reached the culmination of basal area growth; however, more readily available information on spacing and site index can be used to make the same prediction. The results of this study might be most useful to modelers of early stand dynamics in loblolly pine and other commercially important pines.
Biomass Estimation Using the Component Ratio Method for White Oak
DeYoung, Clara (Virginia Tech, 2014-08-26)
With higher demands on biomass, the ability to accurately estimate the amount in a stand is more important now than ever before. Existing models currently in use by the Forest Inventory and Analysis (FIA) program of the United States Department of Agriculture (USDA) Forest Service include the Component Ratio Method (CRM). However, testing of the CRM models is needed to validate and calibrate them. The objective of this research was to test and develop a system of equations capable of producing consistent volume and biomass estimates for standing trees of commercially important hardwood species in the southeastern United States. Testing and comparing was done through use of new and legacy data to establish component ratios of trees and contrast these results to those from existing models. Specifically, analyses were completed for models of merchantable and whole stem volume, wood densities models and averages, and the component ratios for wood, bark, branches, and foliage. The existing models were then calibrated and adjusted. Results on accuracy and fitted results of updated models are reported, along with testing the effects of applying updated models over the state of Virginia.
Coarse Woody Debris in Industrially Managed Pinus taeda Plantations of the Southeastern United States
Pittman, Judd R. (Virginia Tech, 2005-07-15)
Coarse woody debris (CWD) plays an influential role in forested ecosystems by adding organic matter to soils, stabilizing the soil environment, providing wildlife habitat, preventing soil erosion, providing seedling establishment habitat, and involvement in the nutrient cycle. Most CWD research has been conducted in old-growth and unmanaged, second-growth forests. However, less is understood about CWD in intensively managed ecosystems, such as industrialized southern pine plantations. The objectives of this study were to determine the climatic and ecological factors that affect the decomposition rate of CWD, to predict the decomposition rate, specific gravity, and time since death (TSD) using multiple linear regression in industrial loblolly pine (Pinus taeda L.) plantations in the southeastern United States. The study sites for this project were part of a long-term, loblolly pine thinning study maintained by the Loblolly Pine Growth and Yield Research Cooperative at Virginia Tech. Measurements included piece size, position, and decay class. Samples of CWD were collected and analyzed to determine their mass and density. Decomposition rate of CWD was significantly different across position classes and decay classes: disk decomposition rates were significantly negatively correlated with disk diameter, large and small end piece diameter, estimated disk height, and disk dry weight. Average annual precipitation and average annual temperature were not significantly correlated with CWD disk decomposition rate.
Comparing tree foliage biomass models fitted to a multispecies, felled-tree biomass dataset for the United States
Clough, Brian J.; Russell, Matthew B.; Domke, Grant M.; Woodall, Christopher W.; Radtke, Philip J. (2016-08-10)
Estimation of live tree biomass is an important task for both forest carbon accounting and studies of nutrient dynamics in forest ecosystems. In this study, we took advantage of an extensive felled-tree database (with 2885 foliage biomass observations) to compare different models and grouping schemes based on phylogenetic and geographic variation for predicting foliage biomass at the tree scale. We adopted a Bayesian hierarchical statistical framework, first to compare linear models that predict foliage biomass directly to models that separately estimate a foliage ratio as a component of total aboveground biomass, then to compare species specific models to both 'narrow' and 'broad' general biomass models using the best fitted functional form. We evaluated models by simulating new datasets from the posterior predictive distribution, using both summary statistics and visual assessments of model performance. Key findings of our study were: (1) simple linear models provided a better fit to our data than component ratio models, where total biomass and the foliar ratio are estimated separately; (2) species-specific equations provided the best predictive performance, and there was no advantage to narrow species groupings relative to broader groups; and (3) all three model schemes (i.e., species-specific models versus narrow or broad groupings proposed in national-scale biomass equations) tended to over-predict foliage biomass and resulted in predictions with very high uncertainty, particularly for large diameter trees. This analysis represents a fundamental shift in carbon accounting by employing felled-tree data to refine our understanding of uncertainty associated with component biomass estimates, and presents an ideal approach to account for tree-scale allometric model error when estimating forest carbon stocks. However, our results also highlight the need for substantial improvements to both available fitting data and models for foliage biomass before this approach is implemented within the context of greenhouse gas inventories.
Decision Support for Operational Plantation Forest Inventories through Auxiliary Information and Simulation
Green, Patrick Corey (Virginia Tech, 2019-10-25)
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.
Development of Urban Tree Growth Models Based on Site and Soil Characteristics
Wenzel-Bartens, Julia (Virginia Tech, 2010-11-04)
Trees provide numerous benefits crucial to urban environments, yet poor growing conditions often prevent trees from reaching their genetic potential for growth, longevity, and ecosystem function. To overcome these limitations, greater understanding of tree growth in the urban environment is needed. The goal of this research project was therefore to characterize a broad suite of soil characteristics associated with urban tree plantings and evaluate their suitability for modeling physical dimensions and growth rates of urban trees. A series of observational studies and experiments was conducted on urban soils inhabited by two tree species (Zelkova serrata (Thunb.) Mikano and Quercus phellos L.) in Washington, DC and one tree species (Quercus virginiana Mill.) in Jacksonville, FL – two major metropolitan areas of the eastern United States with contrasting climate and soils. Characterization of urban soil attributes within cities revealed low variability for some properties (soil texture, pH, and certain plant nutrients with coefficients of variation (CV) below 0.5), but high variability (CV>1.0) for others (nitrate, ammonium, copper, and zinc). This is dependent on the location. These findings suggest that tree planting site evaluations may not require measurements for all soil properties and that representative sampling may be sufficient to accurately characterize most soil properties within a city. Field assessment of urban tree soils also revealed that conventional measures of soil compaction are difficult to obtain due to obstructions by roots and other foreign objects. To address the critical need for efficient and reliable assessment of soil compaction around urban trees, an experiment was conducted to develop bulk density estimation models for four common soil texture classes using soil strength and soil moisture as predictor variables. These models provided medium (0.42) to high (0.85) coefficients of determination when volumetric water content (VWC) was log transformed, demonstrating that measurements of soil texture, strength, and moisture can provide rapid, reliable assessment of soil compaction. Tree growth modeling focused on three response variables: canopy projection (CP), canopy volume (CV), and peak-increment-area age (PIA). To calculate PIA, tree-ring analysis was used to determine the age at which maximal trunk diameter growth occurred between transplanting and time of sampling. Because Q. virginiana has difficult-to-distinguish growth rings, an intensive tree-ring analysis of cores collected from these trees was conducted. The analysis revealed interseries correlation coefficients of up to 0.66, demonstrating that Q. virginiana can be aged with fairly high confidence in an urban setting. Empirical models developed for all three tree species using the suite of soil and site variables explained 25% – 83% of the observed variability in tree physical dimensions and growth rates. Soil pH was found to be a significant predictor variable for the majority of growth models along with nutrients such as Fe, B, Mn, and Zn, which are also associated with soil alkalinity. Models for PIA possessed the highest coefficient of determination, suggesting that measurements of soil conditions can be used confidently to predict the age at which growth rate subsides in these species. CV and CP were not predicted as well by soil-related variables, presumably because above-ground constraints such as pruning and building encroachment can affect canopy size without necessarily affecting growth rate. Certain prediction models for all three species included predictor variables with counterintuitive influences on tree growth (e.g., negative influences of soil depth on Q. phellos and soil volume on Q. virginiana), suggesting that either these urban trees are responding to these variables in a novel manner or that variables unaccounted for in these models (perhaps related to urbanization or high vehicular traffic) are concomitantly influencing tree growth.
Diameter Distributions of Juvenile Stands of Loblolly Pine (Pinus taeda L.) with Different Planting Densities
Bullock, Bronson P. (Virginia Tech, 2002-02-08)
Diameter distributions of juvenile loblolly pine (Pinus taeda L.) with different planting densities were characterized utilizing a two-parameter Weibull distribution. Trend analysis was employed to describe the effects of planting density, age, relative spacing, and rectangularity on the estimated diameter distributions for juvenile loblolly pine. A reparameterization of the two-parameter Weibull distribution was sought to reduce the dispersion of the estimated shape parameter. Methods that quantify the amount of inter-tree spatial dependency in a particular stand were applied. Empirical semivariograms were derived for each plot over all ages to enable spatial trend recognition. Moran's I and Geary's C coefficients were estimated for ground-line diameters from ages 2 to 5, and for breast height diameters from ages 5 to 11. Though there was no discernable trend in the presence of significant spatial autocorrelation with planting density, an initial negative trend with age was present, but leveled off by age 5. A conditional autoregressive model was utilized to evaluate the amount of spatial influence stems in a stand have on one another. The occurrence of significant spatial influences was positively associated with age through age 8, the trend then leveled off; no recognizable trend was detected with planting density. These indices help to describe stand dynamics that are influenced by the spatial distribution of stems. Models to predict the parameters of the two-parameter Weibull distribution were developed to aid in forecasting and simulation of juvenile loblolly pine. Simulations were conducted where a spatial dependency was imposed on the diameters within a stand. The spatial structure simulation enables accurate representations of stem characteristics when simulating forest stands that include spatially-explicit information.
Dynamic modeling of branches and knot formation in loblolly pine (Pinus taeda L.) trees
Trincado, Guillermo (Virginia Tech, 2006-06-15)
A stochastic framework to simulate the process of initiation, diameter growth, death and self-pruning of branches in loblolly pine (Pinus taeda L.) trees was developed. A data set was obtained from a destructive sampling of whorl sections from 34 trees growing under different initial spacing. Data from dissected branches were used to develop a model for representing knot shape, which assumed that the live portion of a knot can be modeled by a one-parameter equation and the dead portion by assuming a cylindrical shape. For the developed knot model analytical expressions were derived for estimating the volume of knots (live/dead portions) for three types of branch conditions on simulated trees: (i) live branches, (ii) non-occluded dead branches, and (iii) occluded dead branches. This model was intended to recover information on knots shape and volume during the simulation process of branch dynamics. Three different components were modeled and hierarchically connected: whorl, branches and knots. For each new growing season, whorls and branches are assigned stochastically along and around the stem. Thereafter, branch diameter growth is predicted as function of relative location within the live crown and stem growth. Using a taper equation, the spatial location (X,Y,Z) of both live and dead portion of simulated knots is maintained in order to create a 3D representation of the internal stem structure. At the end of the projection period information on (i) vertical trend of branch diameter and location along and around the stem, (ii) volume of knots, and (iii) spatial location, size and type (live and dead) of knots can be obtained. The proposed branch model was linked to the individual-tree growth and yield model PTAEDA3.1 to evaluate the effect of initial spacing and thinning intensity on branch growth in sawtimber trees. The use of the dynamic branch model permitted generation of additional information on sawlog quality under different management regimes. The arithmetic mean diameter of the largest four branches, one from each radial quadrant of the log (i.e. Branch Index, BI) and the number of whorls per log were considered as indicators of sawlog quality. The developed framework makes it possible to include additional wood properties in the simulation system, allowing linkage with industrial conversion processes (e.g. sawing simulation). This integrated modeling system should promote further research to obtain necessary data on crown and branch dynamics to validate the overall performance of the proposed branch model and to improve its components.
Dynamics of Forest Cover Extent, Forest Fragmentation and Their Drivers in the Lake Victoria Crescent, Uganda From 1989 to 2009
Waiswa, Daniel (Virginia Tech, 2011-03-29)
Despite the important values forests play in the tropics, sustainable forest management still remains a challenge as manifested through continued forest loss. The objective of this study was to provide information on the dynamics of forest cover and their drivers vital for enhancing sustainable forest management in the Lake Victoria crescent, Uganda. Several methodologies including remote sensing and Geographic Information Systems techniques, analysis of landscape patterns and various social science techniques were integrated in working towards the stated goal. Results showed that the Lake Victoria crescent, Uganda covering an area of about 1,509,228 ha, experienced a decline in forest cover from 9.0% in 1989 to 4.4% in 2009. This was in comparison with non-forest cover which increased from 58.7% in 1989 to 63.5% in 2009 while open water coverage generally remained unchanged averaging 32.3% from 1989 to 2009. Mean annual deforestation rate from 1989 to 2009 decreased with a weighted mean rate of 2.56%. Both deforestation and afforestation declined between 1989 and 2009 although deforestation still exceeded afforestation. In addition to deforestation, the Lake Victoria crescent also experienced forest fragmentation from 1989 to 2009. Forests greater than 100 ha in size were the most vulnerable to forest fragmentation yet they still constituted a big proportion of forest cover in 2009. Deforestation was a consequence of proximate causes which were triggered by a number of underlying drivers acting singly or in combination, with underlying drivers being more influential. In a bid to promote sustainable forest management, there is a need to continue with efforts to curb deforestation and forest fragmentation, especially amongst forests greater than 100 ha. This could be achieved through empowerment of local communities to take a core role in sustainable management of forest resources.
Effects of uncertainty in upper-stem diameter information on tree volume estimates
Westfall, James A.; McRoberts, Ronald E.; Radtke, Philip J.; Weiskittel, Aaron R. (2016-10)
Almost all relevant data in forestry databases arise from either field measurement or model prediction. In either case, these values have some amount of uncertainty that is often overlooked when doing analyses. In this study, the uncertainty associated with both measured and predicted data was quantified for upper-stem diameter at 5.27 m. This uncertainty was propagated through a tree taper model into predictions of individual-tree volume. The effects of uncertainty on individual-tree volume predictions and population estimates of total volume were assessed. Generally, when little or no systematic measurement deviation was present, less uncertainty was associated with field-measured diameters compared to model predictions. However, diameters predicted from a model were preferred when systematic deviations in field measurement exceeded approximately 0.2 cm. Comparisons of results obtained from an alternative taper model showed that more precise estimates of population totals might be obtained without upper-stem diameter information. Upper-stem diameter information increases the prediction accuracy of individual-tree volume, and thus, models using this information may be preferable in applications such as timber sales containing high-value trees. Due to the various factors that influence measurement and modeling uncertainty, foresters are encouraged to make similar evaluations in the context of their specific activities.
Efficient Sampling Methods for Forest Inventories and Growth Projections
Yang, Sheng-I (Virginia Tech, 2019-06-24)
For operational forest management, a forest inventory is commonly conducted to determine the timber stocking and the value of standing trees in a stand. With time and costs constraints, appropriate sampling designs and models are required to perform the inventory efficiently, as well as to obtain reliable estimates for the variables needed to make projections. In this dissertation research, a simulation study was conducted to extensively explore four important topics in forest inventories: selection of measurement trees in point samples, projection from plot- and stand-level aggregations, subsampling height for volume estimation, and updating stand projections using periodic inventories. A series of simulated loblolly pine plantations with varying degrees of spatial heterogeneity were generated at different stages in stand development. Repeated sampling was used to examine various sampling schemes and growth projection methods. Highlights for the four topics follow: 1. Stand total volume can be reliably estimated using measurement trees tallied by Big BAF, point-double sampling, or random selection of a specified number of trees. However, number of trees per unit area in small-size classes were overestimated across the three tree-selection methods when sample data were aggregated into diameter classes. 2. Plot-level and stand-level projections produced similar estimates for dominant height, basal area, and stems per unit area. As spatial heterogeneity increased, stand-level projections indicated a significant bias of predicted total volume compared with the plot-level projections. 3. Sampling intensity, stand age and spatial heterogeneity have greater influence on the reliability for total volume estimation compared to subsampling intensity and measurement error for height measurements. 4.The variability of total volume estimates increases with increasing projection length (i.e., longer time intervals between inventory entry points). However, the estimates of stand total volume can be greatly improved by updating the models with information obtained in periodic forest inventories, especially when the original models are not well calibrated. The results of this study provide useful guidance and insights for forest practitioners to design forest inventories and improve growth projection systems in operational forest management.
Enhancing the precision of broad-scale forestland removals estimates with small area estimation techniques
Coulston, John W.; Green, P. Corey; Radtke, Philip J.; Prisley, Stephen P.; Brooks, Evan B.; Thomas, Valerie A.; Wynne, Randolph H.; Burkhart, Harold E. (2021-07)
Naional Forest Inventories (NFI) are designed to produce unbiased estimates of forest parameters at a variety of scales. These parameters include means and totals of current forest area and volume, as well as components of change such as means and totals of growth and harvest removals. Over the last several decades, there has been a steadily increasing demand for estimates for smaller geographic areas and/or for finer temporal resolutions. However, the current sampling intensities of many NFI and the reliance on design-based estimators often leads to inadequate precision of estimates at these scales. This research focuses on improving the precision of forest removal estimates both in terms of spatial and temporal resolution through the use of small area estimation techniques (SAE). In this application, a Landsat-derived tree cover loss product and the information from mill surveys were used as auxiliary data for area-level SAE. Results from the southeastern US suggest improvements in precision can be realized when using NFI data to make estimates at relatively fine spatial and temporal scales. Specifically, the estimated precision of removal volume estimates by species group and size class was improved when SAE methods were employed over post-stratified, design-based estimates alone. The findings of this research have broad implications for NFI analysts or users interested in providing estimates with increased precision at finer scales than those generally supported by post-stratified estimators.
Estimating Changes in Residential Water Demand for Voluntary and Mandatory Water-Use Restrictions Implemented during the 2002 Virginia Drought
Halich, Gregory Stewart (Virginia Tech, 2005-06-27)
Municipal water suppliers are increasingly faced with implementing programs to address temporary water shortages in the United States. Having reliable estimates for the effectiveness of these programs will help in water supply planning. This dissertation estimates the reductions in residential water-use for voluntary and mandatory water-use restrictions used in Virginia during the 2002 drought. These restrictions were evaluated using both a conventional approach (single-dummy variable for each) and non-conventional approach where program intensity was accounted for. Program intensity was measured by information dissemination for voluntary restrictions, and by information dissemination and enforcement efforts for mandatory restrictions. An unbalanced panel with data from 21 municipal water suppliers was used in the analysis. Under the conventional approach, voluntary restrictions had no significant effect on water-use and mandatory restrictions showed a small to moderate effect. However, program intensity was found to have a significant influence on the magnitude of the water-use reductions in the non-conventional approach. These reductions ranged from 0-7% for voluntary restrictions, and from 0-22% for mandatory restrictions. Moreover, these reductions followed a pattern of increasing program effectiveness with higher levels of information and enforcement. This result indicates that water supply planners need to give considerable attention to the manner in which drought management programs are implemented. Price was also found to have an important effect on residential water-use. A moderate price increase of $3 per 1000 gallons would be expected to reduce water-use by almost 15%. Thus combining mandatory restrictions (implemented at high intensity) with a moderate to high price increase could result in water-use savings approaching 40% based on estimates from this analysis. Other important findings included: a) consumers were responding to a mix of pure marginal price and fixed fees/previous block rates, b) apartment accounts were found to be included in most of the localities residential data and had a significant impact on water-use, and c) the income parameter was measuring more than a pure income effect.
Estimating individual-tree aboveground biomass of tree species in the western USA
Poudel, Krishna P.; Temesgen, Hailemariam; Radtke, Philip J.; Gray, Andrew N. (2019-06)
Using a large dataset compiled from studies over the years covering 23 tree species, we developed methods to estimate total and components (stem, bark, branch, and foliage) of aboveground live tree biomass. Missing components in the dataset were imputed using species-specific or generalized (species combined into softwood and hardwood groups) Dirichlet imputation. Geometric means of the imputed stem wood proportions were 8% and 9% higher than the observed geometric mean of stem wood proportions in softwood and hardwood species, respectively. For other components, the differences were within 1%. On average, the component ratio method (CRM), used for the official United States forest carbon inventories, underestimated the aboveground biomass (AGB, kg) predictions by 3.7% with a very wide range (-70.3% to 31.6%). Compared with the CRM approach, equations developed in this study reduced RMSE of AGB by as much as 145.0%. On average, new equations reduced RMSE in predicting individual-tree AGB by 15.5% compared with the CRM approach and by 3.9% compared with a calibration of CRM AGB. Predicting AGB as a function of stem volume was not as accurate as using direct AGB equations. Generalized component ratio equations may be suitable for the stem wood component but were highly biased for other components.
Evaluating and improvement of tree stump volume prediction models in the eastern United States
Barker, Ethan Jefferson (Virginia Tech, 2017-06-06)
Forests are considered among the best carbon stocks on the planet. After forest harvest, the residual tree stumps persist on the site for years after harvest continuing to store carbon. A bigger concern is that the component ratio method requires a way to get stump volume to obtain total tree aboveground biomass. Therefore, the stump volumes contribute to the National Carbon Inventory. Agencies and organizations that are concerned with carbon accounting would benefit from an improved method for predicting tree stump volume. In this work, many model forms are evaluated for their accuracy in predicting stump volume. Stump profile and stump volume predictions were among the types of estimates done here for both outside and inside bark measurements. Fitting previously used models to a larger data set allows for improved regression coefficients and potentially more flexible and accurate models. The data set was compiled from a large selection of legacy data as well as some newly collected field measurements. Analysis was conducted for thirty of the most numerous tree species in the eastern United States as well as provide an improved method for inside and outside bark stump volume estimation.
Forest aboveground biomass mapping and estimation across multiple spatial scales using model-based inference
Chen, Qi; McRoberts, Ronald E.; Wang, Changwei; Radtke, Philip J. (2016-10)
Remotely sensed data have been widely used in recent years for mapping and estimating biomass. However, the characterization of the uncertainty of mapped or estimated biomass in previous studies was either based on ad-hoc approaches (e.g., using model fitting statistics such root mean square errors derived from purposive samples) or mostly limited to the analysis of mean biomass for the whole study area. This study proposed a novel uncertainty analysis method that can characterize biomass uncertainty across multiple spatial scales and multiple spatial resolutions. The uncertainty analysis method built on model-based inference and can propagate errors from trees to field plots, individual pixels, and small areas or large regions that consist of multiple pixels (up to all pixels within a study area). We developed and tested this method over northern Minnesota forest areas of approximately 69,508 km(2) via a unique combination of several datasets for biomass mapping and estimation: wall-to-wall airborne lidar data, national forest inventory (NFI) plots, and destructive measurements of tree aboveground biomass (AGB). We found that the pixel-level AGB prediction error is dominated by lidar-based AGB model residual errors when the spatial resolution is near 380 m or finer and by model parameter estimate errors when the spatial resolution is coarser. We also found that the relative error of AGB predicted from lidar can be reduced to approximately 11% (or mean 5.1 Mg/ha; max 43.6 Mg/ha) at one-hectare scale (or at 100 m spatial resolution) over our study area. Because our uncertainty analysis method uses model-based inference and does not require probability samples of field plots, our methodology has potential applications worldwide, especially over tropics and developing countries where NFI systems are not well-established.

Browsing by Author "Radtke, Philip J."

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