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.
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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
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.
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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
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…
Lingzi Wu is an Assistant Professor with the Department of Construction Management (CM) at the University of Washington (UW). Prior to joining UW in September 2022, Dr. Wu served as a postdoctoral fellow in the Department of Civil and Environmental Engineering at University of Alberta, where she received her MSc and PhD in Construction Engineering and Management in 2013 and 2020 respectively. Prior to her PhD, Dr. Wu worked in the industrial construction sector as a project coordinator with PCL Industrial Management from 2013 to 2017.
An interdisciplinary scholar focused on advancing digital transformation in construction, Dr. Wu’s current research interests include (1) integration of advanced data analytics and complex system modeling to enhance construction practices and (2) development of human-in-the-loop decision support systems to improve construction performance (e.g., sustainability and safety). Dr. Wu has published 10 papers in top journals and conference proceedings, including the Journal of Construction Engineering and Management, Journal of Computing in Civil Engineering, and Automation in Construction. Her research and academic excellence has received notable recognition, including a “Best Paper Award” at the 17th International Conference on Modeling and Applied Simulation, and the outstanding reviewer award from the Journal of Construction Engineering and Management.
As an educator and mentor, Dr. Wu aims to create an inclusive, innovative, and interactive learning environment where students develop personal, technical, and transferable skills to grow today, tomorrow, and into the future.
Celina Balderas Guzmán, PhD, is Assistant Professor in the Department of Landscape Architecture. Dr. Balderas’ research spans environmental planning, design, and science and focuses on climate adaptation to sea level rise on the coast and urban stormwater inland. On the coast, her work demonstrates specific ways that the climate adaptation actions of humans and adaptation of ecosystems are interdependent. Her work explores how these interdependencies can be maladaptive by shifting vulnerabilities to other humans or non-humans, or synergistic. Using ecological modeling, she has explored these interdependencies focusing on coastal wetlands as nature-based solutions. Her work informs cross-sectoral adaptation planning at a regional scale.
Inland, Dr. Balderas studies urban stormwater through a social-ecological lens. Using data science and case studies, her work investigates the relationship between stormwater pollution and the social, urban form, and land cover characteristics of watersheds. In past research, she developed new typologies of stormwater wetlands based on lab testing in collaboration with environmental engineers. The designs closely integrated hydraulic performance, ecological potential, and recreational opportunities into one form.
Her research has been funded by major institutions such as the National Science Foundation, National Socio-Environmental Synthesis Center, UC Berkeley, and the MIT Abdul Latif Jameel Water and Food Systems Lab. She has a PhD in the Department of Landscape Architecture and Environmental Planning from the University of California, Berkeley. Previously, she obtained masters degrees in urban planning and urban design, as well as an undergraduate degree in architecture all from MIT.
Narjes Abbasabadi, Ph.D., is an Assistant Professor in the Department of Architecture at the University of Washington. Dr. Abbasabadi also leads the Sustainable Intelligence Lab. Abbasabadi’s research centers on sustainability and computation in the built environment. Much of her work focuses on advancing design research efforts through developing data-driven methods, workflows, and tools that leverage the advances in digital technologies to enable augmented intelligence in performance-based and human-centered design. With an emphasis on multi-scale exploration, her research investigates urban building energy flows, human systems, and environmental and health impacts across scales—from the scale of building to the scale of neighborhood and city.
Abbasabadi’s research has been published in premier journals, including Applied Energy, Building and Environment, Energy and Buildings, Environmental Research, and Sustainable Cities and Society. She received honors and awards, including “ARCC Dissertation Award Honorable Mention” (Architectural Research Centers Consortium (ARCC), 2020), “Best Ph.D. Program Dissertation Award” (IIT CoA, 2019), and 2nd place in the U.S. Department of Energy (DOE)’s Race to Zero Design Competition (DOE, 2018). In 2018, she organized the 3rd IIT International Symposium on Buildings, Cities, and Performance. She served as editor of the third issue of Prometheus Journal, which received the 2020 Haskell Award from AIA New York, Center for Architecture.
Prior to joining the University of Washington, she taught at the University of Texas at Arlington and the Illinois Institute of Technology. She also has practiced with several firms and institutions and led design research projects such as developing design codes and prototypes for low-carbon buildings. Most recently, she practiced as an architect with Adrian Smith + Gordon Gill Architecture (AS+GG), where she has been involved in major projects, including the 2020 World Expo. Abbasabadi holds a Ph.D. in Architecture from the Illinois Institute of Technology and Master’s and Bachelor’s degrees in Architecture from Tehran Azad University.
Dyson, Karen; Yocom, Ken. (2015). Ecological Design For Urban Waterfronts. Urban Ecosystems, 18(1), 189 – 208.
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Abstract
Urban waterfronts are rarely designed to support biodiversity and other ecosystem services, yet have the potential to provide these services. New approaches that integrate ecological research into the design of docks and seawalls provide opportunities to mitigate the environmental impacts of urbanization and recover ecosystem function in urban waterfronts. A review of current examples of ecological design in temperate cities informs suggestions for future action. Conventional infrastructures have significant and diverse impacts on aquatic ecosystems. The impacts of conventional infrastructure are reduced where ecological designs have been implemented, particularly by projects adding microhabitat, creating more shallow water habitat, and reconstructing missing or altered rocky benthic habitats. Opportunities for future research include expanding current research into additional ecosystems, examining ecological processes and emergent properties to better address ecosystem function in ecological design, and addressing the impact of and best practices for continuing maintenance. Planned ecological infrastructure to replace aging and obsolete structures will benefit from design feedback derived from carefully executed in situ pilot studies.
Keywords
Coastal Defense Structures; Fixed Artificial Habitats; Marine Habitats; Intertidal Seawalls; Benthic Communities; Reconciliation Ecology; Subtidal Epibiota; Rocky Shores; Reef; Biodiversity; Ecological Design; Seawalls; Habitat; Waterfront; Urban Infrastructure; Aquatic Ecology
Stewart, Orion T.; Moudon, Anne Vernez; Littman, Alyson J.; Seto, Edmund; Saelens, Brian E. (2018). The Association between Park Facilities and Duration of Physical Activity During Active Park Visits. Journal Of Urban Health, 95(6), 869 – 880.
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Abstract
Public parks provide places for urban residents to obtain physical activity (PA), which is associated with numerous health benefits. Adding facilities to existing parks could be a cost-effective approach to increase the duration of PA that occurs during park visits. Using objectively measured PA and comprehensively measured park visit data among an urban community-dwelling sample of adults, we tested the association between the variety of park facilities that directly support PA and the duration of PA during park visits where any PA occurred. Cross-classified multilevel models were used to account for the clustering of park visits (n=1553) within individuals (n=372) and parks (n=233). Each additional different PA facility at a park was independently associated with a 6.8% longer duration of PA bouts that included light-intensity activity, and an 8.7% longer duration of moderate to vigorous PA time. Findings from this study are consistent with the hypothesis that more PA facilities increase the amount of PA that visitors obtain while already active at a park.
Keywords
Park Facilities; Physical Activity; Park Use; Recreation; Built Environment; Global Positioning System; Accelerometer; Gis; Gps; Accelerometer Data; United-states; Adults; Proximity; Features; Walking; Size; Attractiveness; Improvements; Environment; Parks & Recreation Areas; Parks; Luminous Intensity; Clustering; Urban Areas
Wang, Kaiwen; Liu, Xiaomang; Tian, Wei; Li, Yanzhong; Liang, Kang; Liu, Changming; Li, Yuqi; Yang, Xiaohua. (2019). Pan Coefficient Sensitivity to Environment Variables across China. Journal Of Hydrology, 572, 582 – 591.
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Abstract
Data of open water evaporation (E-ow), such as evaporation of lake and reservoir, have been widely used in hydraulic and hydrological engineering projects, and water resources planning and management in agriculture, forestry and ecology. Because of the low-cost and maneuverability, measuring the evaporation of a pan has been widely regarded as a reliable approach to estimate E-ow through multiplying an appropriate pan coefficient (K-p). K-p is affected by geometry and materials of a pan, and complex surrounding environment variables. However, the relationship between K-p and different environment variables is unknown. Thus, this study chose China D20 pan as an example, used meteorological observations from 767 stations and introduced the latest PenPan model to analyze the sensitivity of K-p to different environment variables. The results show that, the distribution of annual K-p had a strong spatial gradient. For all the stations, annual K-p ranged from 0.31 to 0.89, and decreased gradually from southeast to northwest. The sensitivity analysis shows that for China as a whole, K-p was most sensitive to relative humidity, followed by air temperature, wind speed and sunshine duration. For 767 stations in China, K-p was most sensitive to relative humidity for almost all the stations. For stations north of Yellow River, wind speed and sunshine duration were the next sensitive variables; while for stations south of Yellow River, air temperature was the next sensitive variable. The method introduced in this study could benefit estimating and predicting K-p under future changing environment.
Keywords
Atmospheric Temperature; Hydraulic Engineering; Meteorological Observations; Humidity; Water Supply; Evaporation (meteorology); Sunshine; Lake Management; China; Kp Most Sensitive To Relative Humidity; Open Water Evaporation; Pan Coefficient (kp); Pan Evaporation; Sensitivity Analysis; Reference Evapotranspiration; Reference Crop; Evaporation; Water; Model; Pan Coefficient (k-p); K-p Most Sensitive To Relative Humidity; Air Temperature; Ecology; Forestry; Geometry; Hydrologic Engineering; Lakes; Maneuverability; Meteorological Data; Models; Planning; Prediction; Relative Humidity; Solar Radiation; Wind Speed; Yellow River
Su, Shu; Li, Xiaodong; Zhu, Chen; Lu, Yujie; Lee, Hyun Woo. (2021). Dynamic Life Cycle Assessment: A Review of Research for Temporal Variations in Life Cycle Assessment Studies. Environmental Engineering Science, 38(11), 1013 – 1026.
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Abstract
Life cycle assessment (LCA) is a comprehensive and important environmental management tool around the world. However, lacking temporal information has been a major challenge. In the past decade, dynamic LCA (DLCA), which incorporates temporal variations into assessment, has been an emerging research topic with increasing publications. A timely comprehensive review is needed to present current progress and discuss future directions. This article reviews 144 DLCA articles quantitatively and qualitatively. A bibliometric approach is adopted to conduct co-occurrence analysis and cluster analysis of DLCA studies. The research progress, approaches, and limitations of three temporal variation types (i.e., dynamic life cycle inventory, dynamic characterization factors, and dynamic weighting factors) in DLCA studies are systematically analyzed and discussed. It is concluded that: (1) dynamic inventory analysis is usually conducted by collecting time-differentiated data at each time step. Field monitoring, simulation, scenario analysis, and prediction based on historical data are common approaches. (2) Dynamic characterization studies primarily focus on two impact categories: global warming and toxicity. More studies are in need. (3) Various methods and indicators (i.e., dynamic pollution damage cost, temporal environmental policy targets, and discount rates) are used to solve the dynamic weighting issue, and they have specific limitations. Finally, three interesting topics are discussed: comparison between dynamic and static results, the large data amount issue, and the trend of tools development. This review offers a holistic view on temporal variations in DLCA studies and provides reference and directions for future dynamic studies.
Keywords
Literature Reviews; Cluster Analysis (statistics); Global Warming; Environmental Management; Discount Prices; Emission Inventories; Dynamic Characterization; Dynamic Inventory Analysis; Dynamic Weighting; Environmental Impact; Life Cycle Assessment; Temporal Variation; Cluster Analysis; Life Cycle; 'current; Dynamic Inventory Analyse; Dynamic Lca; Environmental Management Tool; Inventory Analysis; Research Topics; Temporal Information; Dependent Climate Impact; Greenhouse-gas Emission; Biogenic Carbon; Assessment Framework; Fresh-water; Electricity-generation; Energy Efficiency; Wheat Production; Embodied Energy; Time