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.

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.

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.

Background: African American women are one of the least active demographic groups in the US, with only 36% meeting the national physical activity recommendations in comparison to 46% of White women. Physical activity begins to decline in African American women in adolescence and continues to decline into young adulthood. Yet, few interventions have been developed to promote physical activity in African American women during this critical period of life. The purpose of this article was to evaluate the acceptability and feasibility of a culturally-relevant Internet-enhanced physical activity pilot intervention for overweight/obese African American college females and to examine psychosocial and behavioral characteristics associated with intervention adherence and completion.

Methods: A 6-month single group pre-posttest design was used. Participants (n = 27) accessed a culturally-relevant Social Cognitive Theory-based physical activity promotion website while engaging in a minimum of four moderate-intensity physical activity sessions each week. Acceptability and feasibility of the intervention was assessed by participant retention and a consumer satisfaction survey completed by participants.

Results: Fifty-six percent of participants (n = 15) completed the intervention. Study completers were more physically active at baseline (P = 0.05) and had greater social support for exercise from family members (P = 0.04). Sixty percent of study completers (n = 9) reported the website as “enjoyable” or “very enjoyable” to use and 60% (n = 9) reported increased motivation from participation in the physical activity program. Moreover, 87% (n = 13) reported they would recommend the website to a friend.

Conclusions: Results provide some preliminary support for the acceptability and feasibility of an Internet-enhanced physical activity program for overweight/obese African American women, while highlighting important limitations of the approach. Successful promotion of physical activity in college aged African American women as they emerge into adulthood may result in the development of life-long healthy physical activity patterns which may ultimately reduce physical activity-related health disparities in this high risk underserved population. Future studies with larger samples are needed to further explore the use of Internet-based programs to promote physical activity in this population.

Objective: This cross sectional study aims to determine the effects of gender and parental perception of safety at school on children’s physical activity (PA) levels.

Materials and Methods: Parents of school aged Mexican children residing in Guadalajara, Mexico City, and Puerto Vallarta, completed surveys about their children’s PA measures. The physical activity indicators were evaluated using linear and logistical regression models.

Results: Analysis did not indicate that gender moderated the relationship between parental perception of safety and PA measures, but significant gender issues exist with girls participating less than boys in the three measures of PA in this study (p<0.001).

Conclusion: Results suggest the need for additional interventions promoting physical activity in girls in Mexico.

Changes in distribution policies have increased median MELD at transplant with recipients requiring increasing intensive care perioperatively. We aimed to evaluate association of preoperative variables with postoperative respiratory failure (PRF)/increased intensive care unit length of stay (ICU LOS)/short-term survival in a high MELD cohort undergoing liver transplant (LT). Retrospective analysis identified cases of PRF and increased ICU LOS with recipient, donor, and surgical variables examined. Variables were entered into regression with end points of PRF and ICU LOS > 3 days. 164 recipients were examined: 41 (25.0%) experienced PRF and 74 (45.1%) prolonged ICU LOS. Significant predictors of PRF with univariate analysis: BMI > 30, pretransplant MELD, preoperative respiratory failure, LVEF < 50%, FVC < 80%, intraoperative transfusion > 6 units, warm ischemic time > 4 minutes, and cold ischemic time > 240 minutes. On multivariate analysis, only pretransplant MELD predicted PRF (OR 1.14, 𝑝 = 0.01). Significant predictors of prolonged ICU LOS with univariate analysis are as follows: pretransplant MELD, FVC < 80%, FEV1 < 80%, deceased donor, and cold ischemic time > 240 minutes. On multivariate analysis, only pretransplant MELD predicted prolonged ICU LOS (OR 1.28, 𝑝 < 0.001). One-year survival among cohorts with PRF and increased ICU LOS was similar to subjects without. Pretransplant MELD is a robust predictor of PRF and ICU LOS. Higher MELDs at LT are expected to increase need for ICU utilization and modify expectations for recovery in the immediate postoperative period.

Objectives: To determine the off-shift sleep strategies of bi-ethnic night-shift nurses, the relationship between these sleep strategies and adaptation to shift work, and identify the participant-level characteristics associated with a given sleep strategy.

Methods: African-American and non-Hispanic White female, night-shift nurses from an academic hospital were recruited to complete a survey on sleep–wake patterns (n = 213). Participants completed the standard shiftwork index and the biological clocks questionnaire to determine sleep strategies and adaptation to night-shift work. In addition, chronotype was determined quantitatively with a modified version of the Munich ChronoType Questionnaire. Most participants worked ~3 consecutive 12-h night-shifts followed by several days off.

Results: Five sleep strategies used on days off were identified: (a) night stay, (b) nap proxy, (c) switch sleeper, (d) no sleep, and (e) incomplete switcher. Nap proxy and no sleep types were associated with poorer adaptation to night-shift work. The switch sleeper and incomplete switcher types were identified as more adaptive strategies that were associated with less sleep disturbance, a later chronotype, and less cardiovascular problems.

Conclusion: Behavioral sleep strategies are related to adaptation to a typical night-shift schedule among hospital nurses. Nurses are crucial to the safety and well-being of their patients. Therefore, adoption of more adaptive sleep strategies may reduce sleep/wake dysregulation in this population, and improve cardiovascular outcomes.