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<b>REGIONAL DISTRIBUTION OF WOODY INVASIVES AND THE RESPONSE OF PLANT COMMUNITIES TO INVASIVE CONTROL THROUGH GOVERNMENT COST SHARE PROGRAMS</b>Aubrey W Franks (18429756) 24 April 2024 (has links)
<p dir="ltr">Non-native biological invasions are one of the leading concerns for global biodiversity. The establishment of invasive species reduces local biodiversity, shifts species composition, changes successional trajectories, and alters ecosystem functions. This thesis examines two aspects of invasive plants: (1) the distribution and the most important climatic and anthropogenic drivers of invasive trees across the eastern United States, and (2) an evaluation of invasive plant removal and herbaceous recovery from a government cost-share program that provides financial support for invasive plant management by private landowners.</p><p><br></p><p dir="ltr">Our first study focused on identifying the distribution of invasive trees, and the factors associated with their distribution. This is essential to predicting spread and planning subsequent management. Using USDA Forest Inventory Analysis (FIA) data and random forest modeling, we examined the distribution, and variables associated with the distribution, of invasive tree species. Invasive trees were found in 10,511 out of 299,387 FIA plots. Invasive species basal area and density (trees per ha; TPH) were highest within the central and southern Appalachian Mountains, Michigan, the Northeast, and the southern Coastal Plain of the United States. A random forest model of invasive species basal area (R<sup>2 </sup>= 0.47, RMSE = 0.47) and density (R<sup>2</sup>=0.46, RMSE=0.50) vs. environmental variables found that both invasive basal area and density were most strongly associated with human footprint, followed by various climatic variables. An equivalent model of native tree basal (R<sup>2</sup>=0.53, RMSE=9.25) and TPH (R<sup>2</sup>=0.47, RMSE=8.64) found that native tree basal area and density were most strongly associated with aridity followed by various climatic variables. As human footprint increased, invasive tree basal area and density increased. These results suggest that the distribution of invasive trees is reliant on human alterations to forests.</p><p><br></p><p dir="ltr">Our second study focused on Environmental Quality Incentives Program (EQIP), a federal cost-share program that has provided $25 billion of financial assistance to farmers and non-industrial private forest owners. Few studies have examined whether this program facilitates the recovery of the herbaceous layer while decreasing the dominance of invasive plant species. We surveyed the herbaceous layer of EQIP-treated and untreated (reference) forests across three physiographic regions of Indiana. Using non-metric multidimensional scaling (NMDS) ordination and linear mixed effects models, we evaluated the species composition, richness, diversity, evenness, floristic quality index, and herbaceous-layer cover of EQIP and reference sites. We also used linear mixed models to evaluate how EQIP site treatment affected the diversity of native plant species. Sites treated with EQIP contracts typically had significantly higher native species richness, Shannon’s diversity, and floristic quality than reference sites. There were significant separations in species composition between EQIP treated and reference forests state-wide and in the southern non-glaciated region of Indiana, although composition overlapped between EQIP and reference forests. Our study suggests that EQIP-funded treatments promote increased species richness and diversity. However, the persistent overlap in species composition we observed may signify biotic homogenization due to a long-shared history of anthropogenic disturbances between EQIP and reference sites. Therefore, active restoration of the herbaceous layer might be needed to allow a full recovery after invasive removal.</p>
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Dynamics of Forest Ecosystems Under Global Change: Applications of Artificial Intelligence in Mapping, Classification, and ProjectionAkane Ota Abbasi (17123185) 10 October 2023 (has links)
<p dir="ltr">Global forest ecosystems provide essential ecosystem services that contribute to water and climate regulation, food production, recreation, and raw materials. They also serve as crucial habitats for numerous terrestrial species of amphibians, birds, and mammals worldwide. However, recent decades have witnessed unprecedented changes in forest ecosystems due to climate change, shifts in species distribution patterns, increased planted forest areas, and various disturbances such as forest fires, insect infestations, and urbanization. These changes can have far-reaching impacts on ecological networks, human well-being, and the well-being of global forest ecosystems. To address these challenges, I present four studies to quantify forest dynamics through mapping, classification, and projection, using artificial intelligence tools in combination with a vast amount of training data. (I) I present a spatially continuous map of planted forest distribution across East Asia, produced by integrating multiple sources of planted and natural forest data. I found that China contributed 87% of the total planted forest areas in East Asia, most of which are located in the lowland tropical/subtropical regions and Sichuan Basin. I also estimated the dominant genus in each planted forest location. (II) I used continent-wide forest inventory data to compare the range shifts of forest types and their constituent tree species in North America in the past 50 years. I found that forest types shifted more than three times as fast as the average of their constituent tree species. This marked difference was attributable to a predominant positive covariance between tree species ranges and the change of species relative abundance. (III) Based on individual-level field surveys of trees and breeding birds across North America, I characterized New World wood-warbler (<i>Parulidae</i>) species richness and its potential drivers. I identified forest type as the most powerful predictor of New World wood-warbler species richness, which adds valuable evidence to the ongoing physiognomy versus composition debate among ornithologists. (IV) In the appendix, I utilized continent-wide forest inventory data from North America and South America and the combination of supervised and unsupervised machine learning algorithms to produce the first data-driven map of forest types in the Americas. I revealed the distribution of forest types, which are useful for cost-effective forest and biodiversity management and planning. Taken together, these studies provide insight into the dynamics of forest ecosystems at a large geographic scale and have implications for effective decision-making in conservation, management, and global restoration programs in the midst of ongoing global change.</p>
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