APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

A comparison of ground cover and frequency estimation methods for post-harvest soil monitoring

The amount and type of ground cover is an important characteristic to measure when collecting soil disturbance monitoring data after a timber harvest. Estimates of ground cover and bare soil can be used for tracking changes in invasive species, plant growth and regeneration, woody debris loadings, and the risk of surface water runoff and soil erosion. A new method of assessing ground cover and soil disturbance was recently published by the U.S. Forest Service, the Forest Soil Disturbance Monitoring Protocol (FSDMP). This protocol uses the frequency of cover types in small circular (15cm) plots to compare ground surface in pre- and post-harvest condition. While both frequency and percent cover are common methods of describing vegetation, frequency has rarely been used to measure ground surface cover. In this study, three methods for assessing ground cover percent (step-point, 15cm dia. circular and 1x5m visual plot estimates) were compared to the FSDMP frequency method. Results show that the FSDMP method provides significantly higher estimates of ground surface condition for most soil cover types, except coarse wood. The three cover methods had similar estimates for most cover values. The FSDMP method also produced the highest value when bare soil estimates were used to model erosion risk. In a person-hour analysis, estimating ground cover percent in 15cm dia. plots required the least sampling time, and provided standard errors similar to the other cover estimates even at low sampling intensities (n=18). If ground cover estimates are desired in soil monitoring, then a small plot size (15cm dia. circle), or a step-point method can provide a more accurate estimate in less time than the current FSDMP method.

INTERACTIVE EFFECTS OF CLIMATE CHANGE AND FUNGAL COMMUNITIES ON THE DECOMPOSITION OF WOOD-DERIVED CARBON IN FOREST SOILS

Soils are the largest sinks of carbon in terrestrial ecosystems. Soil organic carbon is important for ecosystem balance as it supplies plants with nutrients, maintains soil structure, and helps control the exchange of CO2 with the atmosphere. The processes in which wood carbon is stabilized and destabilized in forest soils is still not understood completely. This study attempts to measure early wood decomposition by different fungal communities (inoculation with pure colonies of brown or white rot, or the original microbial community) under various interacting treatments: wood quality (wood from +CO2, +CO2+O3, or ambient atmosphere Aspen-FACE treatments from Rhinelander, WI), temperature (ambient or warmed), soil texture (loamy or sandy textured soil), and wood location (plot surface or buried 15cm below surface). Control plots with no wood chips added were also monitored throughout the study. By using isotopically-labelled wood chips from the Aspen-FACE experiment, we are able to track wood-derived carbon losses as soil CO2 efflux and as leached dissolved organic carbon (DOC). We analyzed soil water for chemical characteristics such as, total phenolics, SUVA254, humification, and molecular size. Wood chip samples were also analyzed for their proportion of lignin:carbohydrates using FTIR analysis at three time intervals throughout 12 months of decomposition. After two years of measurements, the average total soil CO2 efflux rates were significantly different depending on wood location, temperature, and wood quality. The wood-derived portion soil CO2 efflux also varied significantly by wood location, temperature, and wood quality. The average total DOC and the wood-derived portion of DOC differed between inoculation treatments, wood location, and temperature. Soil water chemical characteristics varied significantly by inoculation treatments, temperature, and wood quality. After 12 months of decomposition the proportion of lignin:carbohydrates varied significantly by inoculation treatment, with white rot having the only average proportional decrease in lignin:carbohydrates. Both soil CO2 efflux and DOC losses indicate that wood location is important. Carbon losses were greater from surface wood chips compared with buried wood chips, implying the importance of buried wood for total ecosystem carbon stabilization. Treatments associated with climate change also had an effect on the level of decomposition. DOC losses, soil water characteristics, and FTIR data demonstrate the importance of fungal community on the degree of decomposition and the resulting byproducts found throughout the soil.

Proteins in silico-modeling and sampling

Proteins are linear chain molecules made out of amino acids. Only when they fold to their native states, they become functional. This dissertation aims to model the solvent (environment) effect and to develop & implement enhanced sampling methods that enable a reliable study of the protein folding problem in silico. We have developed an enhanced solvation model based on the solution to the Poisson-Boltzmann equation in order to describe the solvent effect. Following the quantum mechanical Polarizable Continuum Model (PCM), we decomposed net solvation free energy into three physical terms– Polarization, Dispersion and Cavitation. All the terms were implemented, analyzed and parametrized individually to obtain a high level of accuracy. In order to describe the thermodynamics of proteins, their conformational space needs to be sampled thoroughly. Simulations of proteins are hampered by slow relaxation due to their rugged free-energy landscape, with the barriers between minima being higher than the thermal energy at physiological temperatures. In order to overcome this problem a number of approaches have been proposed of which replica exchange method (REM) is the most popular. In this dissertation we describe a new variant of canonical replica exchange method in the context of molecular dynamic simulation. The advantage of this new method is the easily tunable high acceptance rate for the replica exchange. We call our method Microcanonical Replica Exchange Molecular Dynamic (MREMD). We have described the theoretical frame work, comment on its actual implementation, and its application to Trp-cage mini-protein in implicit solvent. We have been able to correctly predict the folding thermodynamics of this protein using our approach.

Carbon in the Peatlands in the Great Lakes Region

Peatlands cover only ~3% of the global land area, but store ~30% of the worlds' soil carbon. There are many different peat types that store different amounts of carbon. Most inventories of carbon storage in northern peatlands have been conducted in the expansive Sphagnum dominated peatlands. Although, northern white cedar peatlands (NW cedar, Thuja occidentalis L.) are also one of the most common peatland types in the Great Lakes Region, occupying more than 2 million hectares. NW cedar swamps are understudied, due in part to the difficulties in collection methods. General lack of rapid and consistent sampling methods has also contributed in a lack of carbon stock quantification for many peatlands. The main objective of this thesis is to quantify: 1) to evaluate peat sampling methods 2) the amount of C-stored and the rates of long-term carbon accumulation in NW cedar peatlands. We sampled 38 peatlands separated into four categories (black ash, NW cedar swamp, sedge, and Sphagnum) during the summers of 2011/2012 across northern MN and the Upper Peninsula of MI. Basal dates of peat indicate that cedar peatlands were between 1970-7790 years old. Cedar peatlands are generally shallower than Sphagnum peat, but due to their higher bulk density, hold similar amounts of carbon with our sites averaging ~800 MgC ha-1. We estimate that NW cedar peatlands store over 1.7 Gt of carbon in the Great Lakes Region. Each of the six methods evaluated had a different level of accuracy and requires varying levels of effort and resources. The depth only method and intermittent sampling method were the most accurate methods of peatland sampling.

STUDY OF A DIRECT SAMPLING METHOD FOR THE INVERSE MEDIUM SCATTERING PROBLEM

Direct sampling methods are increasingly being used to solve the inverse medium scattering problem to estimate the shape of the scattering object. A simple direct method using one incident wave and multiple measurements was proposed by Ito, Jin and Zou. In this report, we performed some analytic and numerical studies of the direct sampling method. The method was found to be effective in general. However, there are a few exceptions exposed in the investigation. Analytic solutions in different situations were studied to verify the viability of the method while numerical tests were used to validate the effectiveness of the method.

Critical evaluation of diameter increment modelling in the Great Lakes region

Simulations of forest stand dynamics in a modelling framework including Forest Vegetation Simulator (FVS) are diameter driven, thus the diameter or basal area increment model needs a special attention. This dissertation critically evaluates diameter or basal area increment models and modelling approaches in the context of the Great Lakes region of the United States and Canada. A set of related studies are presented that critically evaluate the sub-model for change in individual tree basal diameter used in the Forest Vegetation Simulator (FVS), a dominant forestry model in the Great Lakes region. Various historical implementations of the STEMS (Stand and Tree Evaluation and Modeling System) family of diameter increment models, including the current public release of the Lake States variant of FVS (LS-FVS), were tested for the 30 most common tree species using data from the Michigan Forest Inventory and Analysis (FIA) program. The results showed that current public release of the LS-FVS diameter increment model over-predicts 10-year diameter increment by 17% on average. Also the study affirms that a simple adjustment factor as a function of a single predictor, dbh (diameter at breast height) used in the past versions, provides an inadequate correction of model prediction bias. In order to re-engineer the basal diameter increment model, the historical, conceptual and philosophical differences among the individual tree increment model families and their modelling approaches were analyzed and discussed. Two underlying conceptual approaches toward diameter or basal area increment modelling have been often used: the potential-modifier (POTMOD) and composite (COMP) approaches, which are exemplified by the STEMS/TWIGS and Prognosis models, respectively. It is argued that both approaches essentially use a similar base function and neither is conceptually different from a biological perspective, even though they look different in their model forms. No matter what modelling approach is used, the base function is the foundation of an increment model. Two base functions – gamma and Box-Lucas – were identified as candidate base functions for forestry applications. The results of a comparative analysis of empirical fits showed that quality of fit is essentially similar, and both are sufficiently detailed and flexible for forestry applications. The choice of either base function in order to model diameter or basal area increment is dependent upon personal preference; however, the gamma base function may be preferred over the Box-Lucas, as it fits the periodic increment data in both a linear and nonlinear composite model form. Finally, the utility of site index as a predictor variable has been criticized, as it has been widely used in models for complex, mixed species forest stands though not well suited for this purpose. An alternative to site index in an increment model was explored, using site index and a combination of climate variables and Forest Ecosystem Classification (FEC) ecosites and data from the Province of Ontario, Canada. The results showed that a combination of climate and FEC ecosites variables can replace site index in the diameter increment model.

Assessing visual disturbance conditions on the Custer National Forest

Assessment of soil disturbance on the Custer National Forest was conducted during two summers to determine if the U.S. Forest Service Forest Soil Disturbance Monitoring Protocol (FSDMP) was able to distinguish post-harvest soil conditions in a chronological sequence of sites harvested using different ground-based logging systems. Results from the first year of sampling suggested that the FSDMP point sampling method may not be sensitive enough to measure post-harvest disturbance in stands with low levels of disturbance. Therefore, a revised random transect method was used during the second sampling season to determine the actual extent of soil disturbance in these cutting units. Using combined data collected from both summers I detected statistically significant differences (p < 0.05) in fine fraction bulk density measurements between FSDMP disturbance classes across all sites. Disturbance class 3 (most severe) had the highest reported bulk density, which suggest that the FSDMP visual class estimates are defined adequately allowing for correlations to be made between visual disturbance and actual soil physical characteristics. Forest site productivity can be defined by its ability to retain carbon and convert it to above- and belowground biomass. However, forest management activities that alter basic site characteristics have the potential to alter productivity. Soil compaction is one critical management impact that is important to understand; compaction has been shown to impede the root growth potential of plants, reduce water infiltration rates increasing erosion potential, and alter plant available water and nutrients, depending on soil texture. A new method to assess ground cover, erosion, and other soil disturbances was recently published by the U.S. Forest Service, as the Forest Soil Disturbance Protocol (FSDMP). The FSDMP allows soil scientists to visually assign a disturbance class estimate (0 – none, 1, 2, 3 – severe) from field measures of consistently defined soil disturbance indicators (erosion, fire, rutting, compaction, and platy/massive/puddled structure) in small circular (15 cm) plots to compare soil quality properties pre- and post- harvest condition. Using this protocol we were able to determine that ground-based timber harvesting activities occurring on the Custer National Forest are not reaching the 15% maximum threshold for detrimental soil disturbance outlined by the Region 1 Soil Quality Standards.

Photodegradation and photostabilization of weathered wood flour filled polyethylene composites

Wood plastic composites (WPCs) have gained popularity as building materials because of their usefulness in replacing solid wood in a variety of applications. These composites are promoted as being low-maintenance, high-durability products. However, it has been shown that WPCs exposed to weathering may experience a color change and/or loss in mechanical properties. An important requirement for building materials used in outdoor applications is the retention of their aesthetic qualities and mechanical properties during service life. Therefore, it is critical to understand the photodegradation mechanisms of WPCs exposed to UV radiation and to develop approaches to stabilize these composites (both unstabilized and stabilized) as well as the effect of weathering on the color fade and the retention of mechanical properties were characterized. Since different methods of manufacturing WPCs lead to different surface characteristics, which can influence weathering, the effect of manufacturing method on the photodegradation of WPCs was investigated first. Wood flour (WF) filled high-density polyethylene (HDPE) composite samples were either injection molded, extruded, or extruded and then planed. Fourier transform infrared (FTIR) spectroscopy was used to monitor the surface chemistry of the manufactured composites. The spectra showed that the surface of planed samples had more wood component than extruded and injection molded samples, respectively. After weathering, the samples were analyzed for color fade, and loss of flexural properties. The final lightness of the composites was not dependent upon the manufacturing method. However the mechanical property loss was dependent upon manufacturing method. The samples with more wood component at the surface (planed samples) experienced a larger percentage of total loss in flexural properties after weathering due to a greater effect of moisture on the samples. The change in surface chemistry of HDPE and WF/HDPE composites after weathering was studied using spectroscopic techniques. X-ray photoelectron spectroscopy (XPS) was used to characterize the occurrence of surface oxidation whereas FTIR spectroscopy was used to monitor the development of degradation products, such as carbonyl groups and vinyl groups, and to determine changes in HDPE crystallinity. Surface oxidation occurred immediately after exposure for both the neat HDPE and WF/HDPE composites. After weathering, the surface of the WF/HDPE composites was oxidized to a greater extent than the neat HDPE after weathering. This suggests that photodegradation is exacerbated by the addition of the carbonyl functional groups of the wood fibers within the HDPE atrix during composite manufacturing. While neat HDPE may undergo cross-linking in the initial stages of accelerated weathering, the WF may physically hinder the ability of the HDPE to cross-link resulting in the potential for HDPE chain scission to dominate in the initial weathering stages of the WF/HDPE composites. To determine which photostabilizers are most effective for WF/HDPE composites, factorial experimental designes were used to determine the effects of adding two hindered amine light stabilizers, an ultraviolet absorber, and a pigment on the color made and mechanical properties of both unweathered and UV weathered samples. Both the pigment and ultraviolet absorber were more effective photostabilizers for WF/HDPE composites than hinder amine light stabilizers. The ineffectiveness of hindered amine light stabilizers in protecting WPCs against UV radiation was attribuated to the acid/base reactions occurring between the WF and hindered amine light stabilizer. The efficiency of an ultraviolet absorber and/or pigment was also examined by incorporating different concentration of an ultraviolet absorber and/or pigment into WF/HDPE composites. Color change and flexural properties were determined after accelerated UV weathering. The lightness of the composite after weathering was influenced by the concentration of both the ultraviolet absorber by masking the bleaching wood component as well as blocking UV light. Flexural MOE loss was influenced by an increase in ultraviolet absorber concentration, but increasing pigment concentration from 1 to 2% had little influence on MOE loss. However, increasing both ultraviolet absorber and pigment concentration resulted in improved strength properties over the unstabilized composites after 3000 h of weather. Finally, the change in surface chemistry due to weathering of WF/HDPE composites that were either unstabilized or stabilized with an ultraviolet absorber and/or pigment was analyzed using FTIR spectroscopy. The samples were tested for loss in modulus of elasticity, carbonyl and vinyl group formation at the surface, and change in HDPE crystallinity. It was concluded that structural changes in the samples; carbonyl group formation, terminal vinyl group formation, and crystallinity changes cannot reliably be used to predict changes in modulus of elasticity using a simple linear relationship. The effect of cross-linking, chain scission, and crystallinity changes due to ultraviolet exposure as well as the interfacial degradation due to moisture exposure are inter-related factors when weathering HDPE and WF/HDPE composites.

Comparing remote sensing and ground-based methods of quantifying cover type and carbon storage in an urban forest

Understanding the canopy cover of an urban environment leads to better estimates of carbon storage and more informed management decisions by urban foresters. The most commonly used method for assessing urban forest cover type extent is ground surveys, which can be both timeconsuming and expensive. The analysis of aerial photos is an alternative method that is faster, cheaper, and can cover a larger number of sites, but may be less accurate. The objectives of this paper were (1) to compare three methods of cover type assessment for Los Angeles, CA: handdelineation of aerial photos in ArcMap, supervised classification of aerial photos in ERDAS Imagine, and ground-collected data using the Urban Forest Effects (UFORE) model protocol; (2) to determine how well remote sensing methods estimate carbon storage as predicted by the UFORE model; and (3) to explore the influence of tree diameter and tree density on carbon storage estimates. Four major cover types (bare ground, fine vegetation, coarse vegetation, and impervious surfaces) were determined from 348 plots (0.039 ha each) randomly stratified according to land-use. Hand-delineation was better than supervised classification at predicting ground-based measurements of cover type and UFORE model-predicted carbon storage. Most error in supervised classification resulted from shadow, which was interpreted as unknown cover type. Neither tree diameter or tree density per plot significantly affected the relationship between carbon storage and canopy cover. The efficiency of remote sensing rather than in situ data collection allows urban forest managers the ability to quickly assess a city and plan accordingly while also preserving their often-limited budget.