ASU Scholarship Showcase

The evolution of cooperation is a fundamental problem in biology, especially for non-relatives, where indirect fitness benefits cannot counter within-group inequalities. Multilevel selection models show how cooperation can evolve if it generates a group-level advantage, even when cooperators are disadvantaged within their group. This allows the possibility of group selection, but few examples have been described in nature. Here we show that group selection can explain the evolution of cooperative nest founding in the harvester ant Pogonomyrmex californicus. Through most of this species’ range, colonies are founded by single queens, but in some populations nests are instead founded by cooperative groups of unrelated queens. In mixed groups of cooperative and single-founding queens, we found that aggressive individuals had a survival advantage within their nest, but foundress groups with such non-cooperators died out more often than those with only cooperative members. An agent-based model shows that the between-group advantage of the cooperative phenotype drives it to fixation, despite its within-group disadvantage, but only when population density is high enough to make between-group competition intense. Field data show higher nest density in a population where cooperative founding is common, consistent with greater density driving the evolution of cooperative foundation through group selection.

This paper considers the changes in education and capacity building that are needed in response to environmental and social challenges of the 21st Century. We argue that such changes will require more than adjustments in current educational systems, research funding strategies, and interdisciplinary collaborations. Instead, it calls for a deeper questioning of the assumptions and beliefs that frame both problems and solutions. We first discuss the challenges of transforming education and capacity building within five key arenas: interdisciplinary research; university education systems; primary and secondary education systems; researchers from the developing world; and the public at large and politicians. Our starting point is that any type of revolution that is proposed in response to global change is likely to reflect the educational perspectives and paradigms of those calling for the revolution. We differentiate between a circular revolution (as in the "plan-do-check-act cycle" often used in change management) versus an axial revolution (moving to a different way of thinking about the issues), arguing that the latter is a more appropriate response to the complex transdisciplinary challenges posed by global environmental change. We present some potential tools to promote an axial revolution, and consider the limits to this approach. We conclude that rather than promoting one large and ideologically homogenous revolution in education and capacity building, there is a need for a revolution in the way that leaders working with education and capacity building look at systems and processes of change. From this perspective, transformative learning may not only be desirable, but critical in responding to the challenges posed by global environmental change.

Human societies are unique in the level of cooperation among non-kin. Evolutionary models explaining this behavior typically assume pure strategies of cooperation and defection. Behavioral experiments, however, demonstrate that humans are typically conditional co-operators who have other-regarding preferences. Building on existing models on the evolution of cooperation and costly punishment, we use a utilitarian formulation of agent decision making to explore conditions that support the emergence of cooperative behavior. Our results indicate that cooperation levels are significantly lower for larger groups in contrast to the original pure strategy model. Here, defection behavior not only diminishes the public good, but also affects the expectations of group members leading conditional co-operators to change their strategies. Hence defection has a more damaging effect when decisions are based on expectations and not only pure strategies.

The effects of urbanization on ozone levels have been widely investigated over cities primarily located in temperate and/or humid regions. In this study, nested WRF-Chem simulations with a finest grid resolution of 1 km are conducted to investigate ozone concentrations O₃ due to urbanization within cities in arid/semi-arid environments. First, a method based on a shape preserving Monotonic Cubic Interpolation (MCI) is developed and used to downscale anthropogenic emissions from the 4 km resolution 2005 National Emissions Inventory (NEI05) to the finest model resolution of 1 km. Using the rapidly expanding Phoenix metropolitan region as the area of focus, we demonstrate the proposed MCI method achieves ozone simulation results with appreciably improved correspondence to observations relative to the default interpolation method of the WRF-Chem system. Next, two additional sets of experiments are conducted, with the recommended MCI approach, to examine impacts of urbanization on ozone production: (1) the urban land cover is included (i.e., urbanization experiments) and, (2) the urban land cover is replaced with the region's native shrubland. Impacts due to the presence of the built environment on O₃ are highly heterogeneous across the metropolitan area. Increased near surface O₃ due to urbanization of 10–20 ppb is predominantly a nighttime phenomenon while simulated impacts during daytime are negligible. Urbanization narrows the daily O₃ range (by virtue of increasing nighttime minima), an impact largely due to the region's urban heat island. Our results demonstrate the importance of the MCI method for accurate representation of the diurnal profile of ozone, and highlight its utility for high-resolution air quality simulations for urban areas.

Studies in both terrestrial and aquatic ecosystems have documented the potential importance of consumers on ecosystem-level nutrient dynamics. This is especially true when aggregations of organisms create biogeochemical hotspots through nutrient consumption, assimilation, and remineralization via excretion and egestion. Here, we focused on aggregations of humans in cities to examine how diet and waste management interact to drive nitrogen- (N) and phosphorus- (P) fluxes into nutrient pollution, inert forms, and nutrient recycling. We constructed six diet patterns (five US-based and one developing nation) to examine N- and P-consumption and excretion, and explored their implications for human health. Next, we constructed six waste-management patterns (three US and three for developing nations) to model how decisions at household and city scales determine the eventual fates of N and P. When compared to the US Recommended Daily Intake, all US diet patterns exceeded N and P requirements. Other than the “enriched CO₂ environment scenario” diet, the typical US omnivore had the greatest excess (37% N and 62% P). Notably, P from food additives could account for all of the excess P found in US omnivore and vegetarian diets. Across all waste-management approaches, a greater proportion of P was stored or recycled (0 to > 100% more P than N) and a greater proportion of N was released as effluent (20 to > 100% more N than P) resulting in pollution enriched with N and a recycling stream enriched with P. In developing nations, 60% of N and 50% of P from excreta entered the environment as pollution because of a lack of sanitation infrastructure. Our study demonstrates a novel addition to modeling sustainable scenarios for urban N- and P-budgets by linking human diets and waste management through socio-ecological systems.

On-going efforts to understand the dynamics of coupled social-ecological (or more broadly, coupled infrastructure) systems and common pool resources have led to the generation of numerous datasets based on a large number of case studies. This data has facilitated the identification of important factors and fundamental principles which increase our understanding of such complex systems. However, the data at our disposal are often not easily comparable, have limited scope and scale, and are based on disparate underlying frameworks inhibiting synthesis, meta-analysis, and the validation of findings. Research efforts are further hampered when case inclusion criteria, variable definitions, coding schema, and inter-coder reliability testing are not made explicit in the presentation of research and shared among the research community. This paper first outlines challenges experienced by researchers engaged in a large-scale coding project; then highlights valuable lessons learned; and finally discusses opportunities for further research on comparative case study analysis focusing on social-ecological systems and common pool resources. Includes supplemental materials and appendices published in the International Journal of the Commons 2016 Special Issue. Volume 10 - Issue 2 - 2016.

Governing common pool resources (CPR) in the face of disturbances such as globalization and climate change is challenging. The outcome of any CPR governance regime is the influenced by local combinations of social, institutional, and biophysical factors, as well as cross-scale interdependencies. In this study, we take a step towards understanding multiple-causation of CPR outcomes by analyzing 1) the co-occurrence of Design Principles (DP) by activity (irrigation, fishery and forestry), and 2) the combination(s) of DPs leading to social and ecological success. We analyzed 69 cases pertaining to three different activities: irrigation, fishery, and forestry. We find that the importance of the design principles is dependent upon the natural and hard human made infrastructure (i.e. canals, equipment, vessels etc.). For example, clearly defined social boundaries are important when the natural infrastructure is highly mobile (i.e. tuna fish), while monitoring is more important when the natural infrastructure is more static (i.e. forests or water contained within an irrigation system). However, we also find that congruence between local conditions and rules and proportionality between investment and extraction are key for CPR success independent from the natural and human hard made infrastructure. We further provide new visualization techniques for co-occurrence patterns and add to qualitative comparative analysis by introducing a reliability metric to deal with a large meta-analysis dataset on secondary data where information is missing or uncertain.

Includes supplemental materials and appendices publications in International Journal of the Commons 2016 Special Issue. Volume 10 - Issue 2 - 2016

A relatively unexplored issue in cybersecurity science and engineering is whether there exist intrinsic patterns of cyberattacks. Conventional wisdom favors absence of such patterns due to the overwhelming complexity of the modern cyberspace. Surprisingly, through a detailed analysis of an extensive data set that records the time-dependent frequencies of attacks over a relatively wide range of consecutive IP addresses, we successfully uncover intrinsic spatiotemporal patterns underlying cyberattacks, where the term “spatio” refers to the IP address space. In particular, we focus on analyzing macroscopic properties of the attack traffic flows and identify two main patterns with distinct spatiotemporal characteristics: deterministic and stochastic. Strikingly, there are very few sets of major attackers committing almost all the attacks, since their attack “fingerprints” and target selection scheme can be unequivocally identified according to the very limited number of unique spatiotemporal characteristics, each of which only exists on a consecutive IP region and differs significantly from the others. We utilize a number of quantitative measures, including the flux-fluctuation law, the Markov state transition probability matrix, and predictability measures, to characterize the attack patterns in a comprehensive manner. A general finding is that the attack patterns possess high degrees of predictability, potentially paving the way to anticipating and, consequently, mitigating or even preventing large-scale cyberattacks using macroscopic approaches.

Supply-demand processes take place on a large variety of real-world networked systems ranging from power grids and the internet to social networking and urban systems. In a modern infrastructure, supply-demand systems are constantly expanding, leading to constant increase in load requirement for resources and consequently, to problems such as low efficiency, resource scarcity, and partial system failures. Under certain conditions global catastrophe on the scale of the whole system can occur through the dynamical process of cascading failures. We investigate optimization and resilience of time-varying supply-demand systems by constructing network models of such systems, where resources are transported from the supplier sites to users through various links. Here by optimization we mean minimization of the maximum load on links, and system resilience can be characterized using the cascading failure size of users who fail to connect with suppliers.

We consider two representative classes of supply schemes: load driven supply and fix fraction supply. Our findings are: (1) optimized systems are more robust since relatively smaller cascading failures occur when triggered by external perturbation to the links; (2) a large fraction of links can be free of load if resources are directed to transport through the shortest paths; (3) redundant links in the performance of the system can help to reroute the traffic but may undesirably transmit and enlarge the failure size of the system; (4) the patterns of cascading failures depend strongly upon the capacity of links; (5) the specific location of the trigger determines the specific route of cascading failure, but has little effect on the final cascading size; (6) system expansion typically reduces the efficiency; and (7) when the locations of the suppliers are optimized over a long expanding period, fewer suppliers are required. These results hold for heterogeneous networks in general, providing insights into designing optimal and resilient complex supply-demand systems that expand constantly in time.

n public planning processes for sustainable urban development, planners and experts often face the challenge of engaging a public that is not familiar with sustainability principles or does not subscribe to sustainability values. Although there are calls to build the public’s sustainability literacy through social learning, such efforts require sufficient time and other resources that are not always available. Alternatively, public participation processes may be realigned with the sustainability literacy the participants possess, and their capacity can modestly be built during the engagement. Asking what tools might successfully align public participation with participants’ sustainability literacy, this article describes and evaluates a public participation process in Phoenix, Arizona, in which researchers, in collaboration with city planners, facilitated sustainability conversations as part of an urban development process. The tool employed for Visually Enhanced Sustainability Conversation (VESC) was specifically designed to better align public participation with stakeholders’ sustainability literacy. We tested and evaluated VESC through interviews with participants, city planners, and members of the research team, as well as an analysis of project reports. We found that the use of VESC successfully facilitated discussions on pertinent sustainability issues and embedded sustainability objectives into the project reports. We close with recommendations for strengthening tools like VESC for future public engagements.