Convergence of microclimate in residential landscapes across diverse cities in the United States
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The urban heat island (UHI) is a well-documented pattern of warming in cities relative to rural areas. Most UHI research utilizes remote sensing methods at large scales, or climate sensors in single cities surrounded by standardized land cover. Relatively few studies have explored continental-scale climatic patterns within common urban microenvironments such as residential landscapes that may affect human comfort.
We tested the urban homogenization hypothesis which states that structure and function in cities exhibit ecological “sameness” across diverse regions relative to the native ecosystems they replaced.
We deployed portable micrometeorological sensors to compare air temperature and humidity in residential yards and native landscapes across six U.S. cities that span a range of climates (Phoenix, AZ; Los Angeles, CA; Minneapolis-St. Paul, MN; Boston, MA; Baltimore, MD; and Miami, FL).
Microclimate in residential ecosystems was more similar among cities than among native ecosystems, particularly during the calm morning hours. Maximum regional actual evapotranspiration (AET) was related to the morning residential microclimate effect. Residential yards in cities with maximum AET <50–65 cm/year (Phoenix and Los Angeles) were generally cooler and more humid than nearby native shrublands during summer mornings, while yards in cities above this threshold were generally warmer (Baltimore and Miami) and drier (Miami) than native forests. On average, temperature and absolute humidity were ~6 % less variable among residential ecosystems than among native ecosystems from diverse regions.
These data suggest that common residential land cover and structural characteristics lead to microclimatic convergence across diverse regions at the continental scale.
KeywordsUrban homogenization Residential lawn Microclimate Urban heat island (UHI) Humidity Urban protected area
We are grateful to numerous technical staff, students, and volunteers who assisted with microclimate data collection, including Erin Barton, Matthew Camba, Emma Dixon, La’Shaye Ervin, Caitlin Holmes, Richard McHorney, Miguel Morgan, Joseph Rittenhouse, Anna Royar, Jehane Samaha, Sydney Schiffner, Julea Shaw, Anissa Vega, Elisabeth Ward, and Megan Wheeler. We also thank Darrel Jenerette for reviewing an earlier draft of this manuscript. This project was supported by several collaborative grants from the Macrosystems Biology Program at NSF (EF-1065548, 1065737, 1065740, 1065741, 1065772, 1065785, 1065831, 1241960, and 121238320), and by the Earth Systems Modeling program at NSF (EF-1049251). This work was also supported in part by the NSF Long-term Ecological Research Program in Baltimore (BES LTER, DEB-0423476), Phoenix (CAP LTER, BCS-1026865), Plum Island (PIE LTER Boston; OCE-1058747 and 1238212), Cedar Creek (CDR LTER, Minneapolis–St Paul; DEB-1234162), and Florida Coastal Everglades (FCE LTER, Miami; DBI-0620409).
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