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Residential yards and gardens can have surprisingly high plant diversity. However, we still do not understand all the factors that drive diversity in individual gardens, or how gardens scale up to create larger patterns of urban biodiversity. For example, social interactions between neighbors could affect whether they mimic each other’s yard design, affecting spatial turnover in plant communities. Further, socio-economic differences between neighborhoods might result in distinct plant assemblages across a city. In this paper, we used fieldwork, GIS, and spatial statistics to examine the variability in front yard vegetation—both cultivated and spontaneous plants—in 870 yards in Chicago, Illinois (USA). Our goals were to understand diversity and spatial patterning of plant communities in residential neighborhoods and how they vary with scale, considering alpha, beta, and gamma diversity. We addressed the following questions: (1) How do alpha, beta, and gamma diversity of cultivated and spontaneous plants vary between neighborhoods with different socioeconomic characteristics? (2) Within neighborhoods, do we see spatial autocorrelation in front-yard plant communities? If so, do those spatial patterns affect plant diversity at the neighborhood scale? We found diverse plant communities and distinct spatial patterns across Chicago. Richness and composition of both spontaneous and cultivated plants differed between neighborhoods, with some differences explained by socioeconomic factors such as education. Spontaneous and cultivated plants showed significant spatial autocorrelation, although that spatial autocorrelation generally did not influence neighborhood-scale diversity. Knowledge of these spatial patterns and their socioeconomic drivers could be exploited to increase adoption of environmentally-friendly yard management practices across a city. 

We examine the uneven social and spatial distributions of COVID-19 and their relationships with indicators of social vulnerability in the U.S. epicenter, New York City (NYC). As of July 17th, 2020, NYC, despite having only 2.5% of the U.S. population, has [Formula: see text]6% of all confirmed cases, and [Formula: see text]16% of all deaths, making it a key learning ground for the social dynamics of the disease. Our analysis focuses on the multiple potential social, economic, and demographic drivers of disproportionate impacts in COVID-19 cases and deaths, as well as population rates of testing. Findings show that immediate impacts of COVID-19 largely fall along lines of race and class. Indicators of poverty, race, disability, language isolation, rent burden, unemployment, lack of health insurance, and housing crowding all significantly drive spatial patterns in prevalence of COVID-19 testing, confirmed cases, death rates, and severity. Income in particular has a consistent negative relationship with rates of death and disease severity. The largest differences in social vulnerability indicators are also driven by populations of people of color, poverty, housing crowding, and rates of disability. Results highlight the need for targeted responses to address injustice of COVID-19 cases and deaths, importance of recovery strategies that account for differential vulnerability, and provide an analytical approach for advancing research to examine potential similar injustice of COVID-19 in other U.S. cities. Significance Statement Communities around the world have variable success in mitigating the social impacts of COVID-19, with many urban areas being hit particularly hard. Analysis of social vulnerability to COVID-19 in the NYC, the U.S. national epicenter, shows strongly disproportionate impacts of the pandemic on low income populations and communities of color. Results highlight the class and racial inequities of the coronavirus pandemic in NYC, and the need to unpack the drivers of social vulnerability. To that aim, we provide a replicable framework for examining patterns of uneven social vulnerability to COVID-19- using publicly available data which can be readily applied in other study regions, especially within the U.S.A. This study is important to inform public and policy debate over strategies for short- and long-term responses that address the injustice of disproportionate impacts of COVID-19. Although similar studies examining social vulnerability and equity dimensions of the COVID-19 outbreak in cities across the U.S. have been conducted (Cordes and Castro 2020, Kim and Bostwick 2002, Gaynor and Wilson 2020; Wang et al. 2020; Choi and Unwin 2020), this study provides a more comprehensive analysis in NYC that extends previous contributions to use the highest resolution spatial units for data aggregation (ZCTAs). We also include mortality and severity rates as key indicators and provide a replicable framework that draws from the Centers for Disease Control and Prevention’s Social Vulnerability indicators for communities in NYC. 

Urbanization alters local environmental conditions and the ability of species to disperse between remnant habitat patches within the urban matrix. Nonetheless, despite the ongoing growth of urban areas worldwide, few studies have investigated the relative importance of dispersal and local environmental conditions for influencing species composition within urban and suburban landscapes. Here, we explore this question using spatial patterns of plant species composition.

The Research Triangle area, which includes the cities of Raleigh, Durham, Chapel Hill and Cary, in central North Carolina, USA.

2012–2014.

Vascular plants.

We sampled riparian forest plant communities along an urban‐to‐rural gradient and used redundancy analysis to identify predictors of species composition patterns for groups of species categorized by nativity and seed dispersal mode. We first compared the ability of different models of habitat connectivity (least‐cost paths that avoided urban land cover versus Euclidean and along‐stream distance) to explain spatial patterns of species composition. We then partitioned the variation in species composition explained by habitat connectivity models, local environmental conditions and measures of urbanization in the surrounding landscape.

We found that several groups of native species were best explained by least‐cost path models that avoided urban development, suggesting that urbanization impedes dispersal within this landscape, particularly for short‐dispersed species. Environmental variables related to urbanization (e.g., temperature, stream incision) were important predictors of species composition for many species groups, but measures of urbanization in the surrounding landscape were more important for exotic than for native species.

Our results demonstrate that urbanization influences plant species composition via its effects on both habitat connectivity and environmental conditions. However, the strength of these effects varies somewhat predictably across seed dispersal modes and between native and exotic species. These results highlight the importance of landscape‐scale planning for urban conservation.