A floristic inventory was conducted at Cave Creek Regional Park (CCRP), Maricopa County, AZ. One hundred fifty-four taxa were documented within Park boundaries, including 148 species and six infraspecific taxa in 43 families. Asteraceae, Boraginaceae, and Fabaceae accounted for 40% of documented species and annuals accounted for 56% of documented diversity.
Fire effects were studied at three locations within McDowell Sonoran Preserve (MSP), Scottsdale, AZ. These fires occurred throughout the 1990s and recovered naturally. Fire and reseeding effects were studied at the site of a 2005 fire within CCRP that was reseeded immediately following the fire.
Two questions underlie the study regarding fire and reseeding effects: 1) How did fire and reseeding affect the cover and diversity of the plant communities? 2) Is there a difference in distribution of cover between treatments for individual species or growth habits? To address these questions, I compared burned and adjacent unburned treatments at each site, with an additional reseeded treatment added at CCRP.
MSP sites revealed overall diversity and cover was similar between treatments, but succulent cover was significantly reduced, and subshrub cover was significantly greater in the burn treatment. Seventeen species showed significant difference in distribution of cover between treatments.
The CCRP reseeded site revealed 11 of 28 species used in the seed mix persist 12 years post-fire. The reseeded treatment showed greater overall diversity than burned and unburned treatments. Succulent and shrub cover were significantly reduced by fire while subshrub cover was significantly greater in the reseeded treatment. Sixteen species showed significant difference in distribution of cover between treatments.
Fire appears to impact plant community composition across Arizona Upland sites. Choosing species to include in seed mixes for post-fire reseeding, based on knowledge of pre-fire species composition and individual species’ fire responses, may be a useful tool to promote post-fire plant community recovery.
Fire is a naturally-occurring disruptive ecological force that is an essential part of certain ecosystems, and has historically been a tool used by indigenous fire stewards to maintain the health of the land. In the past century, fire has been severely suppressed throughout many areas of the Western United States as Western colonization and the suppression of native traditional ecological knowledge took place, causing a severe decline in ecosystem health and the accumulation of flammable vegetation, which has more recently contributed towards a frequency of catastrophic, high-intensity wildfires. Current fire management challenges include balancing social and ecological perspectives. In Colorado and other areas of the country, community wildfire protection plans (CWPP) are evolving as a means to involve a variety of community stakeholders in fire management decisions. Using Colorado CWPP boundaries as a social management unit and endangered species ranges as an ecological management unit, I analyzed the spatial overlap of these different factors. Since each CWPP has its own fire management policies, I drew implications from the results for which important factors different CWPPs should consider.
We analyzed multiple different models that can be utilized when measuring effects effects of fire and fire behavior in a forest ecosystem. In the thesis we focused on exploring ordinary differential equations, stochastic models, and partial differential equations
for Unmanned Aerial Vehicles.
Towards enabling a UAV to autonomously sense and avoid moving obstacles, this thesis makes the following contributions. Initially, an image-based reactive motion planner is developed for a quadrotor to avoid a fast approaching obstacle. Furthermore, A Dubin’s curve based geometry method is developed as a global path planner for a fixed-wing UAV to avoid collisions with aircraft. The image-based method is unable to produce an optimal path and the geometry method uses a simplified UAV model. To compensate
these two disadvantages, a series of algorithms built upon the Closed-Loop Rapid Exploratory Random Tree are developed as global path planners to generate collision avoidance paths in real time. The algorithms are validated in Software-In-the-Loop (SITL) and Hardware-In-the-Loop (HIL) simulations using a fixed-wing UAV model and in real flight experiments using quadrotors. It is observed that the algorithm enables a UAV to avoid moving obstacles approaching to it with different directions and speeds.
• Are current college undergraduates interested in the idea of saving for retirement?
• Do they have realistic expectations about how much money they need to save in order to live comfortably during retirement?
• Are there differences in expectations between people who are interested in saving for retirement using traditional means and people who are interested in saving for retirement using the extreme-saving FIRE (Financial Independence Retire Early) method?
This paper examines students’ interest in the idea of saving for retirement through a series of lenses: demographics, financial retirement literacy, and expressed commitment to save for retirement. I hypothesized that traditional retirement expected savers and FIRE expected savers, who correctly answer financial retirement literacy questions, are realistic about how much money they will need to save in order to live comfortably during retirement. To investigate this, a survey was sent out to two ASU Tempe campus business classes; 171 completed responses were analyzed. The statistical analysis of the unfiltered survey results showed three findings, but one finding stood out the most: Students who know what a 401k is (Question 5 in Exhibit 1) are significantly more likely to plan on saving for retirement, when compared to students who don’t know what a 401k is.
When filtering survey results to only show responses from students who know what a 401k is, median responses show that traditional retirement expected savers are somewhat realistic with their retirement savings expectations, while FIRE expected savers are not realistic with their retirement savings expectations.