ASU Scholarship Showcase

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.

Much of the socioeconomic life in the United States occurs in its urban areas. While an urban economy is defined to a large extent by its network of occupational specializations, an examination of this important network is absent from the considerable body of work on the determinants of urban economic performance. Here we develop a structure-based analysis addressing how the network of interdependencies among occupational specializations affects the ease with which urban economies can transform themselves. While most occupational specializations exhibit positive relationships between one another, many exhibit negative ones, and the balance between the two partially explains the productivity of an urban economy. The current set of occupational specializations of an urban economy and its location in the occupation space constrain its future development paths. Important tradeoffs exist between different alternatives for altering an occupational specialization pattern, both at a single occupation and an entire occupational portfolio levels.

The factors that account for the differences in the economic productivity of urban areas have remained difficult to measure and identify unambiguously. Here we show that a microscopic derivation of urban scaling relations for economic quantities vs. population, obtained from the consideration of social and infrastructural properties common to all cities, implies an effective model of economic output in the form of a Cobb-Douglas type production function. As a result we derive a new expression for the Total Factor Productivity (TFP) of urban areas, which is the standard measure of economic productivity per unit of aggregate production factors (labor and capital). Using these results we empirically demonstrate that there is a systematic dependence of urban productivity on city population size, resulting from the mismatch between the size dependence of wages and labor, so that in contemporary US cities productivity increases by about 11% with each doubling of their population. Moreover, deviations from the average scale dependence of economic output, capturing the effect of local factors, including history and other local contingencies, also manifest surprising regularities. Although, productivity is maximized by the combination of high wages and low labor input, high productivity cities show invariably high wages and high levels of employment relative to their size expectation. Conversely, low productivity cities show both low wages and employment. These results shed new light on the microscopic processes that underlie urban economic productivity, explain the emergence of effective aggregate urban economic output models in terms of labor and capital inputs and may inform the development of economic theory related to growth.

An assessment framework was developed to evaluate and characterize material recovery facilities within the U.S. that process e-waste. The framework consists of five key categories including, facility overview, operating model and process flows, product flows, collection methods, and facility resource use. The results were used to conduct a material flow analysis to develop a representative set of end-of-life pathways (e.g., reuse, refurbish, recycle) to better understand the flow of e-waste in the end-of-life management industry. The majority of products collected was from business sector collection routes. The largest number of products (by units) collected at 90% of facilities was mobile phones. It was also seen that most products went directly to recycling for material recovery and were not in the condition to be re-used or refurbished.

Construction waste management has become extremely important due to stricter disposal and landfill regulations, and a lesser number of available landfills. There are extensive works done on waste treatment and management of the construction industry. Concepts like deconstruction, recyclability, and Design for Disassembly (DfD) are examples of better construction waste management methods. Although some authors and organizations have published rich guides addressing the DfD's principles, there are only a few buildings already developed in this area. This study aims to find the challenges in the current practice of deconstruction activities and the gaps between its theory and implementation. Furthermore, it aims to provide insights about how DfD can create opportunities to turn these concepts into strategies that can be largely adopted by the construction industry stakeholders in the near future.

This study assesses whether multifunctional edible landscaping business models provide a sufficient business case at enterprise and city scales to justify widespread implementation. First, semi-structured interviews were conducted with four landscaping entrepreneurs, and the information obtained from the interviews was utilized to carry out a business model comparison with the Business Model Canvas framework. The comparison showed that the landscaping enterprises using multifunctional edible landscaping methods possessed a greater range of value propositions and revenue streams, enhancing their competitive advantage. Second, a GIS landscape analysis of seven Phoenix metro area cities was carried out to identify landscapes that were suited for becoming multifunctional edible landscapes. The GIS analysis identified single family residential, residential recreational open space, municipal parks, and municipal schools as being suitable landscapes, and that the area of these landscapes in the seven cities exceeded 180,000 acres. Third, scenarios were created using interview and GIS data to estimate potential value creation and return on investment of implementing multifunctional edible landscaping in the cities of interest. The scenarios found that the potential value creation of edible landscaping ranged between $3.9 and $66 billion, and that positive return on investment (ROI) could be achieved in 11 out of 12 scenarios within one to five years. Finally, the paper concludes by discussing potential long-term implications of implementing multifunctional edible urban landscaping, as well as possible future directions for multifunctional landscaping business model development and research.

Anthropogenic water sources (AWS) are developed water sources used as a management tool for desert wildlife species. Studies documenting the effects of AWS are often focused on game species; whereas, the effects on non-target wildlife are less understood. We used live trapping techniques to investigate rodent abundance, biomass, and diversity metrics near AWS and paired control sites; we sampled vegetation to determine rodent-habitat associations in the Sauceda Mountains of the Sonoran Desert in Arizona. A total of 370 individual mammals representing three genera and eight species were captured in 4,800 trap nights from winter 2011 to spring 2012.

A multi-response permutation procedure was used to identify differences in small mammal community abundance and biomass by season and treatment. Rodent abundance, biomass, and richness were greater at AWS compared to control sites. Patterns of abundance and biomass were driven by the desert pocket mouse (Chaetodipus penicillatus) which was the most common capture and two times more numerous at AWS compared to controls. Vegetation characteristics, explored using principal components analysis, were similar between AWS and controls. Two species that prefer vegetation structure, Bailey’s pocket mouse (C. baileyi) and white-throated woodrat (Neotoma albigula), had greater abundances and biomass near AWS and were associated with habitat having high cactus density. Although small mammals do not drink free-water, perhaps higher abundances of some species of desert rodents at AWS could be related to artificial structure associated with construction or other resources. Compared to the 30-year average of precipitation for the area, the period of our study occurred during a dry winter. During dry periods, perhaps AWS provide resources to rodents related to moisture.

Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters.

Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions, DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO₂) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6  ×  10⁵ km² region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO₂ enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments.

Predictions of how growth responded to elevated CO₂ strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO₂ study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO₂, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.

The International Long-Term Ecological Research (ILTER) network comprises > 600 scientific groups conducting site-based research within 40 countries. Its mission includes improving the understanding of global ecosystems and informs solutions to current and future environmental problems at the global scales. The ILTER network covers a wide range of social-ecological conditions and is aligned with the Programme on Ecosystem Change and Society (PECS) goals and approach. Our aim is to examine and develop the conceptual basis for proposed collaboration between ILTER and PECS. We describe how a coordinated effort of several contrasting LTER site-based research groups contributes to the understanding of how policies and technologies drive either toward or away from the sustainable delivery of ecosystem services. This effort is based on three tenets: transdisciplinary research; cross-scale interactions and subsequent dynamics; and an ecological stewardship orientation.

The overarching goal is to design management practices taking into account trade-offs between using and conserving ecosystems toward more sustainable solutions. To that end, we propose a conceptual approach linking ecosystem integrity, ecosystem services, and stakeholder well-being, and as a way to analyze trade-offs among ecosystem services inherent in diverse management options. We also outline our methodological approach that includes: (i) monitoring and synthesis activities following spatial and temporal trends and changes on each site and by documenting cross-scale interactions; (ii) developing analytical tools for integration; (iii) promoting trans-site comparison; and (iv) developing conceptual tools to design adequate policies and management interventions to deal with trade-offs. Finally, we highlight the heterogeneity in the social-ecological setting encountered in a subset of 15 ILTER sites. These study cases are diverse enough to provide a broad cross-section of contrasting ecosystems with different policy and management drivers of ecosystem conversion; distinct trends of biodiversity change; different stakeholders’ preferences for ecosystem services; and diverse components of well-being issues.

Differences in governance relationships and community efforts to remove an exotic, rapidly spreading invasive plant, the-mile-a-minute weed (Mikania micrantha), are explored in five case study community forests in the subtropical region of Chitwan, Nepal. An institutional analysis informs an examination of the de jure (formal) versus de facto (on the ground) institutions and actor relationships relevant to Mikania removal efforts. Contrary to the expectations set by the de jure situation, we find heterogeneous governance relationships and norms related to Mikania management across community forests. Content analysis of interview data illuminates reoccurring themes and their implications for social and ecological outcomes in the communities. Complex governance relationships and regular discussion of distrust of government and non-government officials help explain collective action efforts and management decisions. The content analysis suggests that Mikania is impacting people’s daily lives but the degree of severity and the response to the disruption varies substantially and is heavily affected by other problems experienced by community forest members. Our results indicate that understanding how the de facto, or on the ground situation, differs from the de jure institutions may be vital in structuring successful efforts to manage invasive species and understanding collective action problems related to other social-ecological threats. We present data-informed propositions about common pool resource management and invasive species. This study contributes to a better scientific understanding of how institutions mediate social-ecological challenges influencing common pool resources more broadly.