Matching Items (3)
Description
With a growing majority of humans living within cities and towns, urbanization is one of the most persistent drivers of change in global land use and challenges to sustainability and biodiversity conservation. The development of cities and towns can substantially shape local and regional environments in which wildlife communities persist. Although urbanization can negatively affect wildlife communities – through processes such as habitat fragmentation and non-native species introduction – cities can also provide resources to wildlife, such as through food, water, and space, creating potential opportunities for conservation. However, managing wildlife communities persisting in urbanizing landscapes requires better understanding of how urbanized landscapes influence the ability of wildlife to coexist with one another and with people at local and regional scales. In this dissertation, I addressed these research needs by evaluating the environmental and human factors driving dynamic wildlife community distributions and people’s attitudes towards wildlife. In my first two chapters,I used wildlife camera data collected from across the Phoenix Metropolitan Area, AZ to examine seasonal patterns of wildlife space use, species richness, and interspecific interactions across levels of urbanization with varying landscape characteristics, including plant productivity and spatial land use heterogeneity. Here I found that urbanization was a primary driver of wildlife community characteristics within the region, but that seasonal resource availability and landscape heterogeneity could have mediating influences that require further exploration. In my third chapter, I partnered
with wildlife researchers across North America to examine how relationships between urbanization and community composition vary among cities with distinct social-ecological characteristics, finding that effects of local urbanization were more negative in warmer, less vegetated, and more urbanized cities. In my fourth and final chapter, I explored the potential for human-wildlife coexistence by examining how various ideological, environmental, and sociodemographic factors influenced Phoenix area residents’ level of comfort living near different wildlife groups. Although I found that residents’ attitudes were primarily shaped by their relatively static wildlife values, comfort living near wildlife also depended on the characteristics of the neighboring environment, of the residents, and of the wildlife involved, indicating the potential for facilitating conditions for human-wildlife coexistence. Altogether, the findings of this dissertation suggest that the management of wildlife and their interactions with people within cities would benefit from more proactive and holistic consideration of the interacting environmental, wildlife, and human characteristics that influence the persistence of biodiversity within an increasingly urbanized world.
ContributorsHaight, Jeffrey Douglas (Author) / Hall, Sharon J (Thesis advisor) / Lewis, Jesse S (Thesis advisor) / Larson, Kelli L (Committee member) / Wu, Jianguo (Committee member) / Arizona State University (Publisher)
Created2023
Description
As the demand for wireless systems increases exponentially, it has become necessary
for different wireless modalities, like radar and communication systems, to share the
available bandwidth. One approach to realize coexistence successfully is for each
system to adopt a transmit waveform with a unique nonlinear time-varying phase
function. At the receiver of the system of interest, the waveform received for process-
ing may still suffer from low signal-to-interference-plus-noise ratio (SINR) due to the
presence of the waveforms that are matched to the other coexisting systems. This
thesis uses a time-frequency based approach to increase the SINR of a system by estimating the unique nonlinear instantaneous frequency (IF) of the waveform matched
to the system. Specifically, the IF is estimated using the synchrosqueezing transform,
a highly localized time-frequency representation that also enables reconstruction of
individual waveform components. As the IF estimate is biased, modified versions of
the transform are investigated to obtain estimators that are both unbiased and also
matched to the unique nonlinear phase function of a given waveform. Simulations
using transmit waveforms of coexisting wireless systems are provided to demonstrate
the performance of the proposed approach using both biased and unbiased IF estimators.
for different wireless modalities, like radar and communication systems, to share the
available bandwidth. One approach to realize coexistence successfully is for each
system to adopt a transmit waveform with a unique nonlinear time-varying phase
function. At the receiver of the system of interest, the waveform received for process-
ing may still suffer from low signal-to-interference-plus-noise ratio (SINR) due to the
presence of the waveforms that are matched to the other coexisting systems. This
thesis uses a time-frequency based approach to increase the SINR of a system by estimating the unique nonlinear instantaneous frequency (IF) of the waveform matched
to the system. Specifically, the IF is estimated using the synchrosqueezing transform,
a highly localized time-frequency representation that also enables reconstruction of
individual waveform components. As the IF estimate is biased, modified versions of
the transform are investigated to obtain estimators that are both unbiased and also
matched to the unique nonlinear phase function of a given waveform. Simulations
using transmit waveforms of coexisting wireless systems are provided to demonstrate
the performance of the proposed approach using both biased and unbiased IF estimators.
ContributorsGattani, Vineet Sunil (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Richmond, Christ (Committee member) / Maurer, Alexander (Committee member) / Arizona State University (Publisher)
Created2018
Description
With the formation of next generation wireless communication, a growing number of new applications like internet of things, autonomous car, and drone is crowding the unlicensed spectrum. Licensed network such as LTE also comes to the unlicensed spectrum for better providing high-capacity contents with low cost. However, LTE was not designed for sharing spectrum with others. A cooperation center for these networks is costly because they possess heterogeneous properties and everyone can enter and leave the spectrum unrestrictedly, so the design will be challenging. Since it is infeasible to incorporate potentially infinite scenarios with one unified design, an alternative solution is to let each network learn its own coexistence policy. Previous solutions only work on fixed scenarios. In this work we present a reinforcement learning algorithm to cope with the coexistence between Wi-Fi and LTE-LAA agents in 5 GHz unlicensed spectrum. The coexistence problem was modeled as a Dec-POMDP and Bayesian approach was adopted for policy learning with nonparametric prior to accommodate the uncertainty of policy for different agents. A fairness measure was introduced in the reward function to encourage fair sharing between agents. We turned the reinforcement learning into an optimization problem by transforming the value function as likelihood and variational inference for posterior approximation. Simulation results demonstrate that this algorithm can reach high value with compact policy representations, and stay computationally efficient when applying to agent set.
ContributorsSHIH, PO-KAN (Author) / Moraffah, Bahman (Thesis advisor) / Papandreou-Suppappola, Antonia (Thesis advisor) / Dasarathy, Gautam (Committee member) / Shih, YiChang (Committee member) / Arizona State University (Publisher)
Created2021