Matching Items (2)
Filtering by
Description
This project examines a complex issue in urban ecology: the impact of biodiversity on ecosystem services, and considers how this varies across cities. Data were gathered on multiple economic and ecological parameters for a selection of seven cities around the world and analyzed via multiple linear regression in order to assess any relationships that may be at play. Significance values were then calculated to further define the relationships between the data. Analysis found that both biophysical and socioeconomic factors affected ecosystem services, although not all hypotheses regarding these relationships were met. Conclusions indicate that this model was fairly effective in describing physical drivers of ecosystem services, but were not as clear regarding social drivers. Further study regarding social parameters' effect on ecosystem services is recommended.
ContributorsMcDannald, Lindsay JoAnne (Author) / Perrings, Charles (Thesis director) / Kinzig, Ann (Committee member) / Grimm, Nancy (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / School of Sustainability (Contributor)
Created2014-05
Description
This work examines one dimension of the effect that complex human transport systems have on the spread of Chikungunya Virus (CHIKV) in the Caribbean from 2013 to 2015. CHIKV is transmitted by mosquitos and its novel spread through the Caribbean islands provided a chance to examine disease transmission through complex human transportation systems. Previous work by Cauchemez et al. had shown a simple distance-based model successfully predict CHIKV spread in the Caribbean using Markov chain Monte Carlo (MCMC) statistical methods. A MCMC simulation is used to evaluate different transportation methods (air travel, cruise ships, and local maritime traffic) for the primary transmission patterns through linear regression. Other metrics including population density to account for island size variation and dengue fever incidence rates as a proxy for vector control and health spending were included. Air travel and cruise travel were gathered from monthly passenger arrivals by island. Local maritime traffic is approximated with a gravity model proxy incorporating GDP-per-capita and distance and historic dengue rates were used for determine existing vector control measures for the islands. The Caribbean represents the largest cruise passenger market in the world, cruise ship arrivals were expected to show the strongest signal; however, the gravity model representing local traffic was the best predictor of infection routes. The early infected islands (<30 days) showed a heavy trend towards an alternate primary transmission but our consensus model able to predict the time until initial infection reporting with 94.5% accuracy for islands 30 days post initial reporting. This result can assist public health entities in enacting measures to mitigate future epidemics and provide a modelling basis for determining transmission modes in future CHIKV outbreaks.
ContributorsFries, Brendan F (Author) / Perrings, Charles (Thesis director) / Wilson Sayres, Melissa (Committee member) / Morin, Ben (Committee member) / School of Life Sciences (Contributor) / Department of Military Science (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12