Melissa R. McHale

Urban forest biomass estimates: is it important to use allometric relationships developed specifically for urban trees?

Many studies have analyzed the benefits, costs, and carbon storage capacity associated with urban trees. These studies have been limited by a lack of research on urban tree biomass, such that estimates of carbon storage in urban systems have relied upon allometric relationships developed in traditional forests. As urbanization increases globally, it is becoming important to more accurately evaluate carbon dynamics in these systems. Our goal was to understand the variability and range of potential error associated with using allometric relationships developed outside of urban environments. We compared biomass predictions from allometric relationships developed for urban trees in Fort Collins, Colorado to predictions from allometric equations from traditional forests, at both the individual species level and entire communities. A few of the equations from the literature predicted similar biomass to the urban-based predictions, but the range in variability for individual trees was over 300%. This variability declined at increasingly coarse scales, reaching as low as 60% for a street tree community containing 11 tree species and 10, 551 trees. When comparing biomass estimates between cities that implement various allometric relationships, we found that differences could be a function of variability rather than urban forest structure and function. Standardizing the methodology and implementing averaged equations across cities could be one potential solution to reducing variability; however, more accurate quantification of biomass and carbon storage in urban forests may depend on development of allometric relationships specifically for urban trees.

Trees grow on money: Urban tree canopy cover and environmental justice

This study examines the distributional equity of urban tree canopy (UTC) cover for Baltimore, MD, Los Angeles, CA, New York, NY, Philadelphia, PA, Raleigh, NC, Sacramento, CA, and Washington, D.C. using high spatial resolution land cover data and census data. Data are analyzed at the Census Block Group levels using Spearman’s correlation, ordinary least squares regression (OLS), and a spatial autoregressive model (SAR). Across all cities there is a strong positive correlation between UTC cover and median household income. Negative correlations between race and UTC cover exist in bivariate models for some cities, but they are generally not observed using multivariate regressions that include additional variables on income, education, and housing age. SAR models result in higher r-square values compared to the OLS models across all cities, suggesting that spatial autocorrelation is an important feature of our data. Similarities among cities can be found based on shared characteristics of climate, race/ethnicity, and size. Our findings suggest that a suite of variables, including income, contribute to the distribution of UTC cover. These findings can help target simultaneous strategies for UTC goals and environmental justice concerns.

Urban Morphology Drives the Homogenization of Tree Cover in Baltimore, MD, and Raleigh, NC

Heterogeneous land cover patterns contribute to unique ecological conditions in cities and little is known about the drivers of these patterns among cities. We studied tree cover patterns in relationship to urban morphology (for example, housing density, parcel size), socioeconomic factors (for example, education, income, lifestyle characteristics), and historical legacies in Baltimore, Maryland, and Raleigh, North Carolina. Utilizing a multimodel inference approach and bivariate analyses, we analyzed two primary datasets employed in previous research predicting urban tree cover—one comprising continuous data (US Census), and the other consisting of categorical variables (Claritas PRIZM) that incorporate consumer purchasing data. Continuous data revealed that urban morphological characteristics were better predictors of tree cover patterns than socioeconomic factors in Raleigh and Baltimore at the parcel and neighborhood scales. Although the categorical dataset provided some evidence for the importance of socioeconomic and lifestyle characteristics in predicting tree cover patterns, the hierarchical nature of these data preclude separating the impacts of these factors from levels of urbanization. Bivariate analyses of continuous and categorical variables revealed that the highest correlation coefficients were associated with variables describing urban morphology—parcel size, percent pervious area, and house age. In Baltimore, historical census data were better predictors of present-day tree cover than census data from recent years. Most notably, parcel size, a key predictor of tree cover, has decreased with time in Raleigh to sizes consistently seen in Baltimore. Our findings demonstrate that urban morphology, the main driver of tree cover patterns in these cities, may lead to the homogenization of tree canopy in Raleigh and Baltimore in the future.

Practicing the science of sustainability: the challenges of transdisciplinarity in a developing world context

Questions related to how we practice sustainability science remain salient in the face of the failure to achieve broad-scale sustainability objectives. Transdisciplinarity is an essential part of sustainability science. Transdisciplinary conceptual scholarship has been more prevalent than empirical scholarship or applications, especially in developing world contexts. In a single case study of a multiyear project addressing water security issues in HaMakuya, South Africa, we used a framework for assessing transdisciplinary objectives to facilitate more systematic learning for those who practice sustainability science. We found that defining the problem and assembling our team were easier than the co-creation of solution-oriented knowledge and the reintegration and application of this new knowledge. Our singular case study speaks to the potential challenges related to building relationships and co-creating knowledge in an epistemologically diverse setting. Other case studies appear to have negotiated these issues in developing country contexts, and this leaves room further investigation for how to practice transdisciplinarity under these conditions.

Urban Vegetative Cover Fragmentation in the U.S. Associations With Physical Activity and BMI

INTRODUCTION Urban vegetative cover provides a range of ecosystem services including contributions to human health and well-being. Urbanization exerts tremendous pressure on this natural resource, causing fragmentation and loss of urban greenspace. This study aimed to examine associations between vegetative cover fragmentation and physical activity and BMI at the county scale in the U.S. metropolitan statistical areas greater than 1 million in population. METHODS National Land Cover Database 2006 and Behavioral Risk Factor Surveillance System 2008 provided land cover and human health data, respectively. Analyses were performed in 2013 at the county scale where the health data were reported. Spearman rank correlation and stepwise and hierarchical regression models were applied to estimate relationships between land cover and health variables. RESULTS After controlling for median household income and race, greater forest edge density (β=0.272, p<0.05) and larger size of herbaceous patches (β=0.261, p<0.01) were associated with a higher percentage of participation in physical activity within counties. More connections between forest and developed area (β=0.37, p<0.01) and greater edge density of shrubland (β=0.646, p<0.001) were positively associated with a higher percentage of normal BMI (<25) within counties. CONCLUSIONS Forest land cover and some degree of fragmentation are associated with population physical activity. Future studies should examine how built environments and varying land cover configurations influence physical activity and weight status.

Beyond Restoration and into Design: Hydrologic Alterations in Aridland Cities

All cities face the challenge of water provisioning, waste elimination, and stormwater runoff. Historically, these needs have been met by engineered solutions, which although effective, frequently generate unintended negative consequences. These include outcomes such as the loss of water quality improvement by riparian zones and wetlands, elimination of habitat for flora and fauna, and reduced opportunities for urban residents to interact with nature. In an attempt to recapture these and other lost ecosystem services, numerous projects are undertaken to restore aquatic ecosystems in urban areas. It is better to conceive of these interventions as new design initiatives, which, when considered within both local and regional contexts, can potentially re-create lost ecosystem services, as well as introduce new environmental, social, and economic benefits. The approach of ecological design of ecosystem services in streams, though stimulated by projects in an arid zone city, can be applied to urban areas in any region.

Same time, same place: analyzing temporal and spatial trends in urban metabolism using proximate counties in the North Carolina Triangle

Urban ecosystems’ demands for energy and materials are rapidly growing, as is the burden of wastes produced in utilizing these resources. Current consumption patterns are considered unsustainable, as they degrade resource stocks and ecosystem services that support human populations. While an urban metabolism approach is useful in analyzing resource flow dynamics that affect sustainability, challenges regarding data resolution and temporal and spatial consistency have been persistent issues in both time-series and comparative cross-sectional analyses. We envisioned that addressing these issues would allow a deeper examination of changes in metabolic trends and more robust comparison between urban ecosystems. To minimize inconsistencies, we conducted a time-series and cross-sectional metabolism analysis of three proximate urban ecosystems over a common time period. Our study compared the metabolism of Durham, Orange, and Wake Counties in North Carolina, USA using the highest available data resolution from 1985 to 2005. We found that high resolution temporal data made it possible to identify specific metabolic trends and suggest connections to changes in infrastructure, policy, and weather patterns using additional data resources. Analyzing proximate urban ecosystems over a common time period allowed us to identify the metabolic effects of policy, weather patterns, infrastructure, and waste management programs. In evaluating these outcomes, we demonstrate how urban metabolism analyses could be a valuable tool for management and planning related to resource and energy flows.

Relationships between Characteristics of Urban Green Land Cover and Mental Health in U.S. Metropolitan Areas

Urbanization increases risk for depression and other mental disorders. A growing body of research indicates the natural environment confers numerous psychological benefits including alleviation of mental distress. This study examined land cover types and landscape metrics in relation to mental health for 276 U.S. counties within metropolitan areas having a population of 1 million or more. County Health Rankings and Behavioral Risk and Factor Surveillance System (BRFSS) provided a measure of mental health. The 2011 National Land Cover Database (NLCD) provided data on green land cover types, from which seven landscape metrics were generated to characterize landscape patterns. Spearman’s rho correlation and stepwise logistic regression models, respectively, were employed to examine bivariate and multivariate relationships. Models were adjusted for county population and housing density, region, race, and income to account for potential confounding. Overall, individual measures of landscape patterns showed stronger associations with mental health than percent total cover alone. Greater edge contrast was associated with 3.81% lower odds of Frequent Mental Distress (FMD) (Adjusted Odd’s Ratio (AOR) = 0.9619, 95% CI = 0.9371, 0.9860). Shrubland cohesion was associated with greater odds of FMD (AOR = 1.0751, 95% CI = 1.0196, 1.1379). In addition, distance between shrubland cover was associated with greater odds of FMD (AOR = 1.0027, 95% CI = 1.0016, 1.0041). Although effect sizes were small, findings suggest different types of landscape characteristics may have different roles in improving mental health.

Demographic shifts around drinking water supply reservoirs in North Carolina, USA

Infrastructure intended to serve the public good frequently has implications for environmental justice and social sustainability. Drinking water supplies for sub/urban areas in North Carolina, USA, have regularly been secured by constructing dams to impound reservoirs. We used high-resolution, publicly available US Census data to explore whether 66 such reservoirs in North Carolina have induced demographic shifts in the communities that find themselves adjacent to the newly created lakeshores. Our principal findings include: (1) The ratio of white people to non-white people was significantly higher in communities within 0.5 miles of reservoir shorelines than in more distant communities; (2) even as North Carolina overall became less white from 1990 to 2010, the ratio of white people to non-white people within the 0.5 miles of the shoreline increased relative to the overall ratio in the State; and (3) similar, but less distinct, shifts in per capita income occurred during the period. Our results are consistent with the proposition that reservoirs have induced demographic shifts in communities adjacent to newly created lakeshores similar to the shifts associated with environmental gentrification and amenity migration, and may now be associated with perpetuating those shifts. These findings raise concerns about environmental justice and social sustainability that should be considered when planning and building infrastructure that creates environmental amenities. Where reservoirs are being planned, social costs, including the costs of demographic shifts associated with environmental gentrification or amenity migration, and disproportionate regulatory burdens, should be mitigated through innovative policy if possible.

Abiotic Drivers of Ecological Structure and Function in Urban Systems

The interactions between abiotic (nonliving) and biotic (living) factors define ecosystem ecology, and form an essential foundation for any effort to understand urban wildlife. The study of ecosystems considers the flow of energy and materials between organisms and their physical environment. For instance, how much energy enters an ecosystem through the process of primary production—the conversion of CO2, water, and solar energy into biomass—by plants significantly influences how many organisms an ecosystem can support. The interactions between abiotic and biotic components of urban systems are both fundamental to understanding the ecological functioning of cities and are used to explain wildlife-related phenomena, including trophic cascades, biodiversity, and species distribution across the landscape.