Chalana, Manish; Wiser, Jeana C. (2013). Integrating Preservation and Hazard Mitigation for Unreinforced Masonry Buildings in Seattle. APT Bulletin: The Journal Of Preservation Technology, 44(2 – 3), 43 – 51.
Department: Urban Design and Planning
A Global Horizon Scan for Urban Evolutionary Ecology
Verrelli, Brian C.; Alberti, Marina; Des Roches, Simone; Harris, Nyeema C.; Hendry, Andrew P.; Johnson, Marc T. J.; Savage, Amy M.; Charmantier, Anne; Gotanda, Kiyoko M.; Govaert, Lynn; Miles, Lindsay S.; Rivkin, L. Ruth; Winchell, Kristin M.; Brans, Kristien I.; Correa, Cristian; Diamond, Sarah E.; Fitzhugh, Ben; Grimm, Nancy B.; Hughes, Sara; Marzluff, John M.; Munshi-south, Jason; Rojas, Carolina; Santangelo, James S.; Schell, Christopher J.; Schweitzer, Jennifer A.; Szulkin, Marta; Urban, Mark C.; Zhou, Yuyu; Ziter, Carly. (2022). A Global Horizon Scan for Urban Evolutionary Ecology. Trends In Ecology & Evolution, 37(11), 1006-1019.
Abstract
Research on the evolutionary ecology of urban areas reveals how human-induced evolutionary changes affect biodiversity and essential ecosystem services. In a rapidly urbanizing world imposing many selective pressures, a time-sensitive goal is to identify the emergent issues and research priorities that affect the ecology and evolution of species within cities. Here, we report the results of a horizon scan of research questions in urban evolutionary ecology submitted by 100 interdisciplinary scholars. We identified 30 top questions organized into six themes that highlight priorities for future research. These research questions will require methodological advances and interdisciplinary collaborations, with continued revision as the field of urban evolutionary ecology expands with the rapid growth of cities.
Keywords
Urban Ecology; Sustainability; Cities & Towns; Ecosystem Dynamics; Urban Growth; Ecosystem Services; Urban Research; Climate Change; Sociopolitical; Urban Evolution; Urbanization; Human Health; Biodiversity; Adaptation; Challenges; Dynamics; Management; Invasion; Science
A Water Quality Prediction Model for Large-scale Rivers Based on Projection Pursuit Regression in the Yangtze River
Yi, Ze-ji; Yang, Xiao-hua; Li, Yu-qi. (2022). A Water Quality Prediction Model for Large-scale Rivers Based on Projection Pursuit Regression in the Yangtze River. Thermal Science, 26(3), 2561-2567.
Abstract
In recent decades, the Yangtze River Basin, which carries hundreds of millions of people and a substantial economic scale, has been plagued by water quality dete-rioration, threatening considerably sustainable development. In this paper, a sample set is established based on the water quality indexes of chemical oxygen demand and dissolved oxygen obtained by week-by-week monitoring on the main stream of the Yangtze River in Panzhihua, Yueyang, Jiujiang, and Nanjing from 2006 to 2018. The twelve characteristic variables are selected by random forest technique, and the week-by-week dynamic prediction models of chemical oxygen demand and dissolved oxygen at each section of main stream are established by the projection pursuit regression, which can effectively predict the water quality dynamics of the Yangtze River main stream.
Keywords
Pollution; Water Quality; Dynamic Prediction Model; Random Forest; Projection Pursuit Regression; Yangtze River
Associations between Neighborhood Built Environment, Residential Property Values, and Adult BMI Change: The Seattle Obesity Study III
Buszkiewicz, James H.; Rose, Chelsea M.; Ko, Linda K.; Mou, Jin; Moudon, Anne Vernez; Hurvitz, Philip M.; Cook, Andrea J.; Drewnowski, Adam. (2022). Associations between Neighborhood Built Environment, Residential Property Values, and Adult BMI Change: The Seattle Obesity Study III. SSM-Population Health, 19.
Abstract
Objective: To examine associations between neighborhood built environment (BE) variables, residential property values, and longitudinal 1-and 2-year changes in body mass index (BMI). Methods: The Seattle Obesity Study III was a prospective cohort study of adults with geocoded residential addresses, conducted in King, Pierce, and Yakima Counties in Washington State. Measured heights and weights were obtained at baseline (n = 879), year 1 (n = 727), and year 2 (n = 679). Tax parcel residential property values served as proxies for individual socioeconomic status. Residential unit and road intersection density were captured using Euclidean-based SmartMaps at 800 m buffers. Counts of supermarket (0 versus. 1+) and fast-food restaurant availability (0, 1-3, 4+) were measured using network based SmartMaps at 1600 m buffers. Density measures and residential property values were categorized into tertiles. Linear mixed-effects models tested whether baseline BE variables and property values were associated with differential changes in BMI at year 1 or year 2, adjusting for age, gender, race/ethnicity, education, home ownership, and county of residence. These associations were then tested for potential disparities by age group, gender, race/ethnicity, and education. Results: Road intersection density, access to food sources, and residential property values were inversely associated with BMI at baseline. At year 1, participants in the 3rd tertile of density metrics and with 4+ fast-food restaurants nearby showed less BMI gain compared to those in the 1st tertile or with 0 restaurants. At year 2, higher residential property values were predictive of lower BMI gain. There was evidence of differential associations by age group, gender, and education but not race/ethnicity. Conclusion: Inverse associations between BE metrics and residential property values at baseline demonstrated mixed associations with 1-and 2-year BMI change. More work is needed to understand how individual-level sociodemographic factors moderate associations between the BE, property values, and BMI change.
Keywords
Body-mass Index; Physical-activity; Food Environment; Socioeconomic-status; Weight-gain; Health; Quality
Back to the Future: Reintegrating Biology to Understand How Past Eco-evolutionary Change Can Predict Future Outcomes
Thompson, Cynthia L.; Alberti, Marina; Barve, Sahas; Battistuzzi, Fabia U.; Drake, Jeana L.; Goncalves, Guilherme Casas; Govaert, Lynn; Partridge, Charlyn; Yang, Ya. (2022). Back to the Future: Reintegrating Biology to Understand How Past Eco-evolutionary Change Can Predict Future Outcomes. Integrative And Comparative Biology, 61(6), 2218-2232.
Abstract
During the last few decades, biologists have made remarkable progress in understanding the fundamental processes that shape life. But despite the unprecedented level of knowledge now available, large gaps still remain in our understanding of the complex interplay of eco-evolutionary mechanisms across scales of life. Rapidly changing environments on Earth provide a pressing need to understand the potential implications of eco-evolutionary dynamics, which can be achieved by improving existing eco-evolutionary models and fostering convergence among the sub-fields of biology. We propose a new, data-driven approach that harnesses our knowledge of the functioning of biological systems to expand current conceptual frameworks and develop corresponding models that can more accurately represent and predict future eco-evolutionary outcomes. We suggest a roadmap toward achieving this goal. This long-term vision will move biology in a direction that can wield these predictive models for scientific applications that benefit humanity and increase the resilience of natural biological systems. We identify short, medium, and long-term key objectives to connect our current state of knowledge to this long-term vision, iteratively progressing across three stages: (1) utilizing knowledge of biological systems to better inform eco-evolutionary models, (2) generating models with more accurate predictions, and (3) applying predictive models to benefit the biosphere. Within each stage, we outline avenues of investigation and scientific applications related to the timescales over which evolution occurs, the parameter space of eco-evolutionary processes, and the dynamic interactions between these mechanisms. The ability to accurately model, monitor, and anticipate eco-evolutionary changes would be transformational to humanity's interaction with the global environment, providing novel tools to benefit human health, protect the natural world, and manage our planet's biosphere.
Keywords
Rapid Evolution; Ecological Interactions; Niche Construction; Climate-change; Phenotype; Community; Selection; Fitness; Consequences; Variability
Qing Shen awarded funding for commute research survey
The Mobility Innovation Center announced that Qing Shen, professor of Urban Design & Planning and an expert in transportation planning and policy, has received a $100,000 award to study commuting patterns and develop a model to understand the effect of telework and flexible scheduling. The project will build off the existing Commute Trip Reduction (CTR) survey for employers who are in the CTR program as required by state law in the central city portion of Seattle. In addition, a complementary…
Dylan Stevenson
Dylan Stevenson’s (Prairie Band Potawatomi descent) research examines how culture informs planning strategies and influences land relationships. More specifically, he investigates how tribal epistemologies structure notions of Indigenous futurities by centering Indigenous cultural values at the forefront of environmental stewardship and cultural preservation. He is currently working on a project researching how governments (Federal, State, and Tribal) embed cultural values in Water Resources Planning strategies, drawing from ethnographic research he conducted in the joint territory of the United Keetoowah Band of Cherokee Indians and Cherokee Nation in Oklahoma. His other research interests include ecological restoration, intangible cultural heritage, and food systems planning. Previously, Dylan has worked for public and quasi-public entities dealing with the implementation and compliance of local, state, and federal legislation in California and has forthcoming work analyzing Diversity, Equity, and Inclusion (DEI) initiatives in planning programs.
Dylan earned his Ph.D. in the Department of City and Regional Planning at Cornell University. He earned his master’s degree in Planning with a concentration in Preservation and Design of the Built Environment from the University of Southern California, a bachelor’s degree in Linguistics with a minor in Native American Studies from the University of California—Davis, and an associate of arts degree in Liberal Arts from De Anza College.
College of Built Environments’ Research Restart Fund Awards Four Grants in First of Two Cycles
The College of Built Environments launched a funding opportunity for those whose research has been affected by the ongoing pandemic. The Research Restart Fund, with awards up to $5,000, has awarded 4 grants in its first of two cycles. A grant was awarded to Real Estate faculty member Arthur Acolin, who is partnering with the City of Seattle’s Office of Planning and Community Development to understand barriers that homeowners, particularly those with lower incomes, face to building Accessory Dwelling Units…
Assessing Multifamily Residential Parking Demand and Transit Service
Rowe, Daniel H.; Bae, Chang-hee Christine; Shen, Qing. (2010). Assessing Multifamily Residential Parking Demand and Transit Service. Ite Journal-institute Of Transportation Engineers, 80(12), 20 – 24.
Abstract
This study examined the relationship of multifamily residential parking demand and transit level of service in Two King County, WA, USA, Urban Centers: First Hill/Capitol Hill (FHCH) and redmond. In addition, current parking policies were assessed for their ability to meet the observed parking demand, and an alternative method to collect parking demand data was explored.
Exposure of Bicyclists to Air Pollution in Seattle, Washington Hybrid Analysis Using Personal Monitoring and Land Use Regression
Hong, E-Sok Andy; Bae, Christine. (2012). Exposure of Bicyclists to Air Pollution in Seattle, Washington Hybrid Analysis Using Personal Monitoring and Land Use Regression. Transportation Research Record, 2270, 59 – 66.
Abstract
The increase in urban bicycling facilities, raises public health concerns for potential exposure of bicyclists to traffic emissions. For an assessment of bicyclists' exposure to local traffic emissions, a hybrid approach is presented; it combines personal monitoring and a land use regression (LUR) model. Black carbon, a proxy variable for traffic-related air pollution, was measured with an Aethalometer along the predesignated bicycle route in Seattle, Washington, for 10 days, during a.m. and p.m. peak hours (20 sampling campaigns). Descriptive statistics and three-dimensional pollution maps were used to explore temporal variations and to identify pollution hot spots. The LUR model was developed to quantify the influence of spatial covariates on black carbon concentrations along the designated route. The results indicated that the black carbon concentrations fluctuated throughout the sampling periods and showed statistically significant diurnal and monthly patterns. The hot spot analysis suggests that proximity to traffic and other physical environments have important impacts on bicyclists' exposure and demand further investigation on the localized effects of traffic emissions on exposure levels. The LUR model explains 46% of the variations in black carbon concentrations, and significant relationships are found with types of bicycle route facility, wind speed, length of truck routes, and transportation and utility land uses. This research is the first application of the LUR approach in quantifying bicyclists' exposure to air pollution in transport microenvironments. This study provides a rationale for encouraging municipalities to develop effective strategies to mitigate the health risks of exposure to local traffic emissions in complex urban bicycling environments.
Keywords
Particulate Matter; Diesel Exhaust; Health; Model; Particles; Asthma; City