This study investigated the effect of environmental heat stress on physiological and performance measures during a ~4 mi time trial (TT) mountain hike in the Phoenix metropolitan area. Participants (n = 12; 7M/5F; age 21.6 ± 2.47 [SD]) climbed ‘A’ mountain (~1 mi) four times on a hot day (HOT; wet bulb globe temperature [WBGT] = 31.6°C) and again on a moderate day (MOD; WBGT = 19.0°C). Physiological and performance measures were made before and throughout the course of each hike. Mean pre-hike hydration status (urine specific gravity [USG]) indicated that participants began both HOT and MOD trials in a euhydrated state (1.016 ± 0.010 and 1.010 ± 0.008, respectively) and means did not differ significantly between trials (p = .085). Time trial performance was impaired by -11% (11.1 minutes) in the HOT trial (105 ± 21.7 min), compared to MOD (93.9 ± 13.1 min) (p = .013). Peak core temperatures were significantly higher in HOT (38.5 ± 0.36°C) versus MOD (38.0 ± 0.30°C) with progressively increasing differences between trials over time (p < .001). Peak ratings of perceived exertion were significantly higher in HOT (14.2 ± 2.38) compared to MOD (11.9 ± 2.02) (p = .007). Relative intensity (percent of age-predicted maximal heart rate [HR]), estimated absolute intensity (metabolic equivalents [METs]), and estimated energy expenditure (MET-h) were all increased in HOT, but not significantly so. The HOT condition reduced predicted maximal aerobic capacity (CRFp) by 6% (p = .026). Sweat rates differed significantly between HOT (1.38 ± 0.53 L/h) and MOD (0.84 ± 0.27 L/h) (p = .01). Percent body mass loss (PBML) did not differ significantly between HOT (1.06 ± 0.95%) and MOD (0.98 ± 0.84%) (p = .869). All repeated measures variables showed significant between-subjects effects (p < .05), indicating individual differences in response to test conditions. Heat stress was shown to negatively affect physiological and performance measures in recreational mountain hikers. However, considerable variation exists between individuals, and the degree of physiological and performance impairment is probably due, in part, to differences in aerobic fitness and acclimatization status rather than pre- or during-performance hydration status.

The Maricopa County Heat Relief Network (HRN) is an ad-hoc partially self-organized network with some attributes of hierarchical coordination that forms each year to provide heat relief and hydration to residents in need by operating as cooling centers. These HRN organizations are a collection of non-profit, governmental and religious organizations. This dissertation looks at the HRN from a complexity governance perspective and engaged different parts of the network in interviews to learn more about their perspective in delivering heat relief. Further, participatory modeling with a prototype agent based model was done with the HRN coordinating agencies to look for emergent outcomes in the HRN system and learn from their perspective. Chapter one evaluates organizational theory and complexity with climate adaptation, hazard preparedness and resilience in the HRN. Chapter two presents results from interviews with HRN facility managers and evaluates their perspective on how they function to offer heat relief. Chapter three finds that the HRN is a good example of complexity governance when engaged through a participatory agent based modeling approach. Chapter four engages the HRN coordinators in participatory agent based modeling interviews to increase their systems level awareness, learn about their perspective on heat relief delivery, and how the system can be improved. Chapter five looks across the different levels of the HRN investigated, the facility managers and coordinators, for differences and similarities in perspectives. The research conducted in this dissertation shows different levels of systems awareness of the different parts of the HRN and how participatory modeling can be used to increase systems awareness. Results indicate that there was very little horizontal network connection between HRN facility managers and most of the interaction was vertically coordinated indicating opportunities for increased network communication in the future both horizontally and vertically if communication interventions were put in place.

Many coastal cities around the world are becoming increasingly vulnerable to natural disasters, particularly flooding driven by tropical storm and hurricane storm surge – typically the most destructive feature of these storms, generating significant economic damage and loss of life. This increase in vulnerability is driven by the interactions between a wide number of complex social and climatic factors, including population growth, irresponsible urban development, a decrease in essential service provision, sea level rise, and changing storm regimes. These issues are exacerbated by the short-term strategic planning that dominates political action and economic decision-making, resulting in many vulnerable coastal communities being particularly unprepared for large, infrequent storm surge events. This lack of preparedness manifests in several ways, but one of the most visible is the lack of comprehensive evacuation and rescue operation plans for use after major storm surge flooding occurs. Typical evacuation or rescue plans are built using a model of a region’s intact road network. While useful for pre-disaster purposes, the immediate aftermath of large floods sees enormous swaths of a given region’s road system flooded, rendering most of these plans largely useless. Post-storm evacuation and rescue requires large amounts of atypical travel through a region (i.e., across non-road surfaces). Traditional road network models (such as those that are used to generate evacuation routes) are unable to conceptualize this type of transportation, and so are of limited utility during post-disaster scenarios. To solve these problems, this dissertation introduces an alternative network conceptualization that preserves important on-network information but also accounts for the possibility of off-network travel during a disaster. Providing this in situ context is necessary to adequately model transportation through a post-storm landscape, one in which evacuees and rescuers are regularly departing from roads and one in which many roads are completely interdicted by flooding. This modeling approach is used to automatically generate routes through a flooded coastal urban area, as well as to identify potentially critical road segments in advance of an actual storm. These tools may help both emergency managers better prepare for large storms, and urban planners in their efforts to mitigate flood damage.