The growing disconnect between humans and nature has implications for human well-being. Research has linked exposure to nature with various benefits including improved focus, vitality, productivity, and reduced stress, factors that may enhance the academic performance of individual students. In intensively-urbanized landscapes with few natural elements this effect could, via aggregated population-level impacts, influence the academic performance of entire populations, negatively affecting educational attainment and propagating urban poverty. Designing urban environments to provide increased interaction with natural landscape elements such as vegetation could mitigate this effect, benefiting the academic growth and future success of urban students. Recent studies support this idea; however, this effect is poorly understood, hindering the management of urban environments to improve educational outcomes. This study explores relationships between urban nature and the academic performance of urban schools using the Twin Cities Metropolitan Area of Minnesota, USA as a case study area. We used regression analysis to identify relationships among environmental variables on and around school campuses (i.e., tree cover, vegetated land covers, water) and four measures of populationlevel third-grade reading and mathematics success, accounting for school socioeconomic and demographic characteristics. Contrary to expectations, we found a positive relationship between impervious surfaces and reading performance, while relationships between two vegetated land covers (grass, shrub) and water bodies and both mathematics and reading academic success were non-significant. We found a significant, positive relationship between tree cover and reading performance, suggesting that initiatives aimed at increasing tree cover in student environments could support academic success.

Urban greenspace benefits urbanites in numerous ways ranging from regulating flooding, air quality, and local climate to providing opportunities for exercise and relaxation. These benefits may influence human health. Greenspace, for example, may facilitate exercise, thereby helping to reduce body mass index (BMI) and combat obesity, a current epidemic of great public health concern. Little evidence exists to support this assertion, however, and we lack a full understanding of the mechanisms whereby this relationship operates, the populations for whom greenspace is linked to weight status, and the aspects of urban greenspace that are linked to weight status. This study seeks to identify relationships among the composition and arrangement of greenspace and BMI for different populations using regression models for eight age and gender groups in Cleveland, Ohio, US. We find that several greenspace variables are related to BMI for women under 65 years and males under 51 years, but not for older groups, and that the aspects and types of greenspace that are significantly related to BMI vary among groups. Relationships between greenspace attributes and BMI are generally stronger for female groups and for younger groups. Providing access to greenspace with particular attributes such as greenspaces with water, canopy cover, or connected greenspaces could support a healthy weight status for some populations, but these attributes are not consistent across age and gender groups. These results could help to inform policy aimed at designing urban greenspace to benefit the health of different population subgroups.

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Summary Cities are becoming increasingly important to biodiversity conservation, conservation that could also benefit urban people given the importance of nature to human well-being. Urban conservation is challenging, however, given cities’ primary role as human habitats and the need to simultaneously support heterogeneous human and wild species communities in similarly heterogeneous environments. We demonstrate a framework for identifying conservation zones within cities and human and species habitat preferences within them, thereby identifying habitat attributes that management could target to support human well-being and conservation objectives. The framework first categorizes conservation zones within a city, then develops species indicator communities for each zone. Habitat preferences are identified for each indicator community using richness modelling, and human habitat preferences within zones are identified using one of several approaches. Lastly, habitat preferences are compared to identify commonalities and differences within zones. We demonstrate our framework in Iowa City (IA, USA) using songbirds, identifying similarities in human and bird habitat preferences within conservation zones that management could target to support human well-being and species conservation and differences in preferences that could be proactively managed to reduce conflict. This framework can thus identify key habitat attributes and approaches to inform conservation planning targeted to specific settings within cities.