An ecology of prestige in New York City: examining the relationships among population density, socio-economic status, group identity, and residential canopy cover.

Several social theories have been proposed to explain the uneven distribution of vegetation in urban residential areas: population density, social stratification, luxury effect, and ecology of prestige. We evaluate these theories using a combination of demographic and socio-economic predictors of vegetative cover on all residential lands in New York City. We use diverse data sources including the City's property database, time-series demographic and socio-economic data from the US Census, and land cover data from the University of Vermont's Spatial Analysis Lab (SAL). These data are analyzed using a multi-model inferential, spatial econometrics approach. We also examine the distribution of vegetation within distinct market categories using Claritas' Potential Rating Index for Zipcode Markets (PRIZM™) database. These categories can be disaggregated, corresponding to the four social theories. We compare the econometric and categorical results for validation. Models associated with ecology of prestige theory are more effective for predicting the distribution of vegetation. This suggests that private, residential patterns of vegetation, reflecting the consumption of environmentally relevant goods and services, are associated with different lifestyles and lifestages. Further, our spatial and temporal analyses suggest that there are significant spatial and temporal dependencies that have theoretical and methodological implications for understanding urban ecological systems. These findings may have policy implications. Decision makers may need to consider how to most effectively reach different social groups in terms of messages and messengers in order to advance land management practices and achieve urban sustainability.

Variation the in relationship between urban tree canopy and air temperature reduction under a range of daily weather conditions.

Mitigating heat is a vital ecosystem service of trees, particularly with climate change. Land surface temperature measures captured at a single time of day (in the morning) dominate the urban heat island literature. Less is known about how local tree canopy and impervious surface regulate air temperature throughout the day, and/or across many days with varied weather conditions, including cloud cover. We use bike-mounted air temperature sensors throughout the day in New Haven, Connecticut, USA, from 2019 to 2021 and generalized additive mixed models across 156 rides to estimate the daily variation in cooling benefits associated with tree canopy cover, and warming from impervious surface cover in 90 m buffers surrounding bike observations. Cooling is inferred by subtracting the bicycle-observed temperature from a reference station. The cooling benefits from tree canopy cover were strongest in the midday (11:00-14:00, -1.62 °C), afternoon (14:00-17:00, -1.19 °C), and morning (8:00-11:00, -1.15 °C) on clear days. The cooling effect was comparatively smaller on cloudy mornings -0.92 °C and afternoons -0.51 °C. Warming from impervious surfaces was most pronounced in the evening (17:00-20:00, 1.11 °C) irrespective of clouds, and during cloudy nights (20:00-23:00) and cloudy mornings 1.03 °C 95 % CI [1.03, 1.04]. Among the hottest observed days (top 25th percentile of reference station daily maxima), tree canopy was associated with lower temperatures on clear afternoons -1.78 °C [-1.78, -1.78], cloudy midday -1.17 °C [-1.19, -1.15], clear midday -1.12 °C [-1.12, -1.11]. We add a broader spectrum of weather conditions by explicitly including clouds, and greater temporal resolution by measuring throughout the day to bike-based urban heat research. Future mobile sampling campaigns may broaden the spatial extent with more environmental variation, representing an opportunity for public science and engagement.

Gauging the happiness benefit of US urban parks through Twitter.

The relationship between nature contact and mental well-being has received increasing attention in recent years. While a body of evidence has accumulated demonstrating a positive relationship between time in nature and mental well-being, there have been few studies comparing this relationship in different locations over long periods of time. In this study, we analyze over 1.5 million tweets to estimate a happiness benefit, the difference in expressed happiness between in- and out-of-park tweets, for the 25 largest cities in the US by population. People write happier words during park visits when compared with non-park user tweets collected around the same time. While the words people write are happier in parks on average and in most cities, we find considerable variation across cities. Tweets are happier in parks at all times of the day, week, and year, not just during the weekend or summer vacation. Across all cities, we find that the happiness benefit is highest in parks larger than 100 acres. Overall, our study suggests the happiness benefit associated with park visitation is on par with US holidays such as Thanksgiving and New Year's Day.

Spatial changes in park visitation at the onset of the pandemic.

The COVID-19 pandemic disrupted the mobility patterns of a majority of Americans beginning in March 2020. Despite the beneficial, socially distanced activity offered by outdoor recreation, confusing and contradictory public health messaging complicated access to natural spaces. Working with a dataset comprising the locations of roughly 50 million distinct mobile devices in 2019 and 2020, we analyze weekly visitation patterns for 8,135 parks across the United States. Using Bayesian inference, we identify regions that experienced a substantial change in visitation in the first few weeks of the pandemic. We find that regions that did not exhibit a change were likely to have smaller populations, and to have voted more republican than democrat in the 2020 elections. Our study contributes to a growing body of literature using passive observations to explore who benefits from access to nature.

Urban tree canopy and asthma, wheeze, rhinitis, and allergic sensitization to tree pollen in a New York City birth cohort.

BACKGROUND: Urban landscape elements, particularly trees, have the potential to affect airflow, air quality, and production of aeroallergens. Several large-scale urban tree planting projects have sought to promote respiratory health, yet evidence linking tree cover to human health is limited. OBJECTIVES: We sought to investigate the association of tree canopy cover with subsequent development of childhood asthma, wheeze, rhinitis, and allergic sensitization. METHODS: Birth cohort study data were linked to detailed geographic information systems data characterizing 2001 tree canopy coverage based on LiDAR (light detection and ranging) and multispectral imagery within 0.25 km of the prenatal address. A total of 549 Dominican or African-American children born in 1998-2006 had outcome data assessed by validated questionnaire or based on IgE antibody response to specific allergens, including a tree pollen mix. RESULTS: Tree canopy coverage did not significantly predict outcomes at 5 years of age, but was positively associated with asthma and allergic sensitization at 7 years. Adjusted risk ratios (RRs) per standard deviation of tree canopy coverage were 1.17 for asthma (95% CI: 1.02, 1.33), 1.20 for any specific allergic sensitization (95% CI: 1.05, 1.37), and 1.43 for tree pollen allergic sensitization (95% CI: 1.19, 1.72). CONCLUSIONS: Results did not support the hypothesized protective association of urban tree canopy coverage with asthma or allergy-related outcomes. Tree canopy cover near the prenatal address was associated with higher prevalence of allergic sensitization to tree pollen. Information was not available on sensitization to specific tree species or individual pollen exposures, and results may not be generalizable to other populations or geographic areas.

Predicting opportunities for greening and patterns of vegetation on private urban lands.

This paper examines predictors of vegetative cover on private lands in Baltimore, Maryland. Using high-resolution spatial data, we generated two measures: "possible stewardship," which is the proportion of private land that does not have built structures on it and hence has the possibility of supporting vegetation, and "realized stewardship," which is the proportion of possible stewardship land upon which vegetation is growing. These measures were calculated at the parcel level and averaged by US Census block group. Realized stewardship was further defined by proportion of tree canopy and grass. Expenditures on yard supplies and services, available by block group, were used to help understand where vegetation condition appears to be the result of current activity, past legacies, or abandonment. PRIZM market segmentation data were tested as categorical predictors of possible and realized stewardship and yard expenditures. PRIZM segmentations are hierarchically clustered into 5, 15, and 62 categories, which correspond to population density, social stratification (income and education), and lifestyle clusters, respectively. We found that PRIZM 15 best predicted variation in possible stewardship and PRIZM 62 best predicted variation in realized stewardship. These results were further analyzed by regressing each dependent variable against a set of continuous variables reflective of each of the three PRIZM groupings. Housing age, vacancy, and population density were found to be critical determinants of both stewardship metrics. A number of lifestyle factors, such as average family size, marriage rates, and percentage of single-family detached homes, were strongly related to realized stewardship. The percentage of African Americans by block group was positively related to realized stewardship but negatively related to yard expenditures.