ASU Scholarship Showcase

Successful careers in sustainability are determined by positive real-world change towards sustainability. This success depends heavily on professional skills in effective and compassionate communication, collaborative teamwork, or impactful stakeholder engagement, among others. These professional skills extend beyond content knowledge and methodical expertise. Current sustainability programs do not sufficiently facilitate students’ acquisition of such skills. This article presents a brief summary of professional skills, synthesized from the literature, and why they are relevant for sustainability professionals. Second, it presents how these skills have been taught in an undergraduate course in sustainability at Arizona State University, USA. Third, it critically discusses the effectiveness and challenges of that exemplary course. Finally, the article concludes with outlining the lessons learned that should be incorporated into future course offerings.

Resilience can have desirable and undesirable consequences. Thus, resilience should not be viewed as a normative desirable goal, but as a descriptor of complex systems dynamics. From this perspective, we apply resilience thinking concepts to assess the dynamics of inequality, spatial segregation, and sustainability in Chile’s capital city of Santiago. Chile’s economy boosted since democracy was restored in 1990, but continuity of neoliberal reforms and transformations of Pinochet’s dictatorship (1973–1990) seem to have locked Chilean cities in resilient, albeit unsustainable, patterns of uneven development. Socio-economic data from Santiago shows highly resilient patterns of urban inequality and segregation from 1992 to 2009 despite democratic efforts, political agendas and discourses packed with calls for reducing poverty and inequality. We present a conceptual model based on the notion of stability landscapes to explore potential trade-offs between resilience and sustainable development. We mapped Santiago’s spatio-temporal inequality trends and explored if these patterns support an inequality-resilience stability landscape. Analysis of temporal and spatial distribution of development assets across four human development dimensions (i.e., income, education, health, democracy) revealed potential socio-political and spatial feedbacks supporting the resilience of inequality and segregation in Santiago. We argue that urban sustainability may require breaking this resilience, a process where bottom-up stressors such as social movements could play a key role.

This paper aims to contribute to the evolving literature on the new landscape of scholarly journals. It builds on a series of experiences as a journal editor which span the print and digital eras, and focuses on two current activities with new journals. One was designed as a synoptic journal in a broad multidisciplinary field, supported by a commercial publisher; the other a non-revenue journal which aims to showcase the work of undergraduates in the author’s institution. Despite the uniqueness of goals and delivery, some of the experiences—and challenges—have proved remarkably similar.

In order to improve the efficiency of government spending, it is necessary for the decentralized irrigation management to gain support from local institutions. Efficient institutions take on several distinct configurations in different irrigation districts. In this research, we upgrade Tang’s (1992) framework focusing on incentives, to a framework that includes institutional incentives and coordination. Within the framework, we then classify 5 institutional variables: water pricing reform (P), government funding (F), coordination by administration (C), having formal monitors (M) and self-organized management (S). This article processes the data obtained through a field survey (2009–2011) in 20 of China’s southern counties, where they implement the “Small-scale Irrigation and Water Conservancy Key Counties Construction (Key Counties Construction)”, a national project supported by the central government. Next, it applies Data Envelopment Analysis (DEA) to measure the efficiency of government spending and uses Qualitative Comparative Analysis (QCA) to extract efficient institutional configurations. It concludes that there are generally three types of institutional configurations able to improve the efficiency of government spending, which are respectively: “government funding combined with coordination by administration”, “water pricing reform combined with self-organized management and coordination by administration or water pricing reform combined with self-organized management and government funding and formal monitors” and “self-organized management”. Among these, the second configuration is a mixed governance structure with multiple institutions coexisting, and this configuration occurs in the most efficient key counties. For that reason, it is viewed as the mainstream irrigation management approach, and we expect it to be the development trend in the future. Although Chinese irrigation policies are formalizing effective local institutions, they are still not sufficient. Future policies are needed to 1) promote institutions of government support for water laws in order to build stable expectations for both water user associations (WUAs) and farmers, 2) guide water pricing reform by ensuring farmers’ water rights and regulating water markets, and 3) provide opportunities for hiring professional monitors and crafting formal rules.

Many population centers in the American West rely on water from the Colorado River Basin, which has faced shortages in recent years that are anticipated to be exacerbated by climate change. Shortages to urban water supplies related to climate change will not be limited to cities dependent on the Colorado River. Considering this, addressing sustainable water governance is timely and critical for cities, states, and regions facing supply shortages and pollution problems. Engaging in sustainability transitions of these hydro-social systems will increase the ability of such systems to meet the water needs of urban communities. In this paper, we identify historical transitions in water governance and examine their context for three sites in the Colorado River Basin (Denver, Colorado, Las Vegas, Nevada, and Phoenix, Arizona) to provide insight for intentional transitions towards sustainable, or “water sensitive” cities. The comparative historical approach employed allows us to more fully understand differences in present-day water governance decisions between the sites, identify past catalysts for transitions, and recognize emerging patterns and opportunities that may impact current and future water governance in the Colorado River Basin and beyond.

Health systems are heavily promoting patient portals. However, limited health literacy (HL) can restrict online communication via secure messaging (SM) because patients’ literacy skills must be sufficient to convey and comprehend content while clinicians must encourage and elicit communication from patients and match patients’ literacy level. This paper describes the Employing Computational Linguistics to Improve Patient-Provider Secure Email (ECLIPPSE) study, an interdisciplinary effort bringing together scientists in communication, computational linguistics, and health services to employ computational linguistic methods to (1) create a novel Linguistic Complexity Profile (LCP) to characterize communications of patients and clinicians and demonstrate its validity and (2) examine whether providers accommodate communication needs of patients with limited HL by tailoring their SM responses. We will study >5 million SMs generated by >150,000 ethnically diverse type 2 diabetes patients and >9000 clinicians from two settings: an integrated delivery system and a public (safety net) system. Finally, we will then create an LCP-based automated aid that delivers real-time feedback to clinicians to reduce the linguistic complexity of their SMs. This research will support health systems’ journeys to become health literate healthcare organizations and reduce HL-related disparities in diabetes care.

Increasing temperatures have been shown to impact soil biogeochemical processes, although the corresponding changes to the underlying microbial functional communities are not well understood. Alterations in the nitrogen (N) cycling functional component are particularly important as N availability can affect microbial decomposition rates of soil organic matter and influence plant productivity. To assess changes in the microbial component responsible for these changes, the composition of the N-fixing (nifH), and denitrifying (nirS, nirK, nosZ) soil microbial communities was assessed by targeted pyrosequencing of functional genes involved in N cycling in two major biomes where the experimental effect of climate warming is under investigation, a tallgrass prairie in Oklahoma (OK) and the active layer above permafrost in Alaska (AK). Raw reads were processed for quality, translated with frameshift correction, and a total of 313,842 amino acid sequences were clustered and linked to a nearest neighbor using reference datasets. The number of OTUs recovered ranged from 231 (NifH) to 862 (NirK). The N functional microbial communities of the prairie, which had experienced a decade of experimental warming were the most affected with changes in the richness and/or overall structure of NifH, NirS, NirK and NosZ. In contrast, the AK permafrost communities, which had experienced only 1 year of warming, showed decreased richness and a structural change only with the nirK-harboring bacterial community. A highly divergent nirK-harboring bacterial community was identified in the permafrost soils, suggesting much novelty, while other N functional communities exhibited similar relatedness to the reference databases, regardless of site. Prairie and permafrost soils also harbored highly divergent communities due mostly to differing major populations.

MALDI-TOF MS has been utilized as a reliable and rapid tool for microbial fingerprinting at the genus and species levels. Recently, there has been keen interest in using MALDI-TOF MS beyond the genus and species levels to rapidly identify antibiotic resistant strains of bacteria. The purpose of this study was to enhance strain level resolution for Campylobacter jejuni through the optimization of spectrum processing parameters using a series of designed experiments. A collection of 172 strains of C. jejuni were collected from Luxembourg, New Zealand, North America, and South Africa, consisting of four groups of antibiotic resistant isolates. The groups included: (1) 65 strains resistant to cefoperazone (2) 26 resistant to cefoperazone and beta-lactams (3) 5 strains resistant to cefoperazone, beta-lactams, and tetracycline, and (4) 76 strains resistant to cefoperazone, teicoplanin, amphotericin, B and cephalothin.

Initially, a model set of 16 strains (three biological replicates and three technical replicates per isolate, yielding a total of 144 spectra) of C. jejuni was subjected to each designed experiment to enhance detection of antibiotic resistance. The most optimal parameters were applied to the larger collection of 172 isolates (two biological replicates and three technical replicates per isolate, yielding a total of 1,031 spectra). We observed an increase in antibiotic resistance detection whenever either a curve based similarity coefficient (Pearson or ranked Pearson) was applied rather than a peak based (Dice) and/or the optimized preprocessing parameters were applied. Increases in antimicrobial resistance detection were scored using the jackknife maximum similarity technique following cluster analysis. From the first four groups of antibiotic resistant isolates, the optimized preprocessing parameters increased detection respective to the aforementioned groups by: (1) 5% (2) 9% (3) 10%, and (4) 2%. An additional second categorization was created from the collection consisting of 31 strains resistant to beta-lactams and 141 strains sensitive to beta-lactams. Applying optimal preprocessing parameters, beta-lactam resistance detection was increased by 34%. These results suggest that spectrum processing parameters, which are rarely optimized or adjusted, affect the performance of MALDI-TOF MS-based detection of antibiotic resistance and can be fine-tuned to enhance screening performance.

Specification of PM_2.5 transmission characteristics is important for pollution control and policymaking. We apply higher-order organization of complex networks to identify major potential PM_2.5 contributors and PM_2.5 transport pathways of a network of 189 cities in China. The network we create in this paper consists of major cities in China and contains information on meteorological conditions of wind speed and wind direction, data on geographic distance, mountains, and PM_2.5 concentrations. We aim to reveal PM_2.5 mobility between cities in China. Two major conclusions are revealed through motif analysis of complex networks. First, major potential PM_2.5 pollution contributors are identified for each cluster by one motif, which reflects movements from source to target. Second, transport pathways of PM_2.5 are revealed by another motif, which reflects transmission routes. To our knowledge, this is the first work to apply higher-order network analysis to study PM_2.5 transport.

To investigate dual-process persuasion theories in the context of group decision making, we studied low and high need-for-cognition (NFC) participants within a mock trial study. Participants considered plaintiff and defense expert scientific testimony that varied in argument strength. All participants heard a cross-examination of the experts focusing on peripheral information (e.g., credentials) about the expert, but half were randomly assigned to also hear central information highlighting flaws in the expert’s message (e.g., quality of the research presented by the expert). Participants rendered pre- and post-group-deliberation verdicts, which were considered “scientifically accurate” if the verdicts reflected the strong (versus weak) expert message, and “scientifically inaccurate” if they reflected the weak (versus strong) expert message. For individual participants, we replicated studies testing classic persuasion theories: Factors promoting reliance on central information (i.e., central cross-examination, high NFC) improved verdict accuracy because they sensitized individual participants to the quality discrepancy between the experts’ messages. Interestingly, however, at the group level, the more that scientifically accurate mock jurors discussed peripheral (versus central) information about the experts, the more likely their group was to reach the scientifically accurate verdict. When participants were arguing for the scientifically accurate verdict consistent with the strong expert message, peripheral comments increased their persuasiveness, which made the group more likely to reach the more scientifically accurate verdict.