Browsing by Subject "Forest Inventory"

Now showing 1 - 3 of 3
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    Advancing Estimation Of Timber Products Output In The Lake States Region Of The Northern United States
    (2019-05) Young, John
    The Forest Inventory and Analysis (FIA) – Timber Products Output (TPO) program has chosen to implement a sampling design for collecting information from primary wood-using facilities across the US. Sample-based approaches are often clear alternatives to surveys, as they offer estimates with increased precision and quantifiable error at lower costs and greater speed. Coulston et al. (2018) has selected a unique stratified random sampling design, which separates mills into a “certainty” or “uncertainty” sample based on a measure of size (MOS). However, the new design is in its early stages and needs for developing the efficiency of the design have been identified. This research assesses the advancement of two key areas: the selection of an effective MOS and the identification of a threshold for allocating mills into a “certainty” sample. When sampling highly-skewed populations, a few large units may account for large portions of the mean estimated and incorrectly accounting for these units can negatively impact the precision of estimation. Systematic identification of a certainty threshold was assessed through methods inspired by the work of Glasser (1962) and Hidiroglou (1985). Estimates produced by these methods were analyzed against historic TPO data to assess for overall impact. MOS also alter the precision, and as the correlation between the variable of interest and the MOS increases the level of uncertainty tends to decrease. Sources for gathering auxiliary mill metrics were explored and relevant attributes were combined to create MOS using three separate techniques: correlation comparison, simple linear regression, and multiple regression. The implementation of different MOS and threshold identification techniques, their impact on sampling efficiency, and potential areas of further research are assessed.
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    Post-stratified estimation of Coarse Woody debris Volume using the down woody materials sample of forest inventory and analysis.
    (2010-05) Hatfield, Mark A.
    The Forest Inventory and Analysis (FIA) program of the USDA Forest Service conducts a nation wide survey of America’s forests. FIA field crews collect data on tree size, condition, and species, as well as data on the conditions in which they grow from a network of permanent ground plots known as Phase two plots (P2). FIA crews also collect more detailed forest health indicators, including data on Coarse Woody Materials (CWD), on a 1 16 subset of the P2 sample. This subset is known as the Phase 3 (P3) sample. FIA regularly publishes reports on the quantity and quality of America’s forests using data from the P2 sample. A post-stratified estimation technique is used increase the precision of the estimates without increasing the sample size. Currently, research on how to best apply the post-stratified estimator to produce estimates of the P3 forest health indicators has been lacking. This thesis will address this gap by testing 18 candidate geospatial layers (both categorical and continuous) as stratification layers to produce estimates of CWD volume in the Lake-states region of Minnesota, Wisconsin, and Michigan. Continuous geospatial layers will be broken into two to five strata using an optimization algorithm. A simulation experiment is used estimate the long term effectiveness of successful geospatial layers. The simulation experiment is performed to compare the conditional and unconditional variance estimators of the post-stratified estimators. Successful geospatial layers are then applied to sub-populations of varying sizes to determine the effect of spatial extent on the post-stratification method. Stratification layers derived from remote sensing products provided the best results. Using two or three strata is recommended because further partition of the population simply produces ineffective sliver strata. No difference was detected between the two competing variance estimators. The effect of spatial extent of the stratification was volatile. The use of large spatial extents is recommended. The conclusion of this thesis summarizes the lessons learned throughout as well as ideas for future research on the topic.
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    Stand Dynamics and Stand Development of Conventional and Mixedwood Aspen Systems in Northern Minnesota
    (2024-05) Semper, Chelsea
    In northern Minnesota, white spruce (Picea glauca (Moench) Voss) and aspen (Populus tremuloides Michx) mixedwood forests are important for timber production and ecological services. Traditionally grown in monoculture stands, little is known about the regeneration, growth, and yield of these species when managed in mixed compositions. 20 pure aspen and 20 mixedwood stands within a chronosequence of 0 – 23 years old in northern Minnesota were sampled to investigate stand differences. Forest inventory data were collected on seedlings, saplings, overstory trees, and non-tree understory cover, and forest modeling was conducted in Forest Vegetation Simulator (FVS) to simulate stand growth under different management scenarios. While aspen stands had higher density at regeneration and merchantable yield at harvest, mixedwoods maintained greater compositional and structural diversity throughout the rotation. Overall, white spruce-aspen mixedwood systems can provide opportunities for increased ecological services during early stand development without compromising on long-term timber-focused management goals.