Globally, rivers are being heavily dammed and over-utilized to the point where water shortages are starting to occur. This problem is magnified in arid and semi-arid regions where climate change, growing populations, intensive agriculture and urbanization have created tremendous pressures on existing river systems. Regulatory incentives have been enacted in recent decades that have spurred river restoration programs in the United States. But what kind of governance does river restoration require that is different from allocative institutional set-ups? Are these recovery programs succeeding in restoring ecological health and resilience of the rivers? Do the programs contribute to social-ecological resilience of the river systems more broadly? This study aims to tackle these key questions for two Colorado River sub-basin recovery programs (one in the Upper Basin and one in the Lower Basin) through utilization of different frameworks and methodologies for each. Organizational resilience to institutional and biophysical disturbances varies, with the Upper Basin program being more resilient than the Lower Basin program. Ecological resilience as measured by beta diversity (for the Upper Basin) was a factor of the level of hydrological and technological interventions rather than an occurrence of the natural flow regime. This points to the fact that in a highly-dampened and managed system like the Colorado River, the dampened flow regime alone is not a significant factor in maintaining community diversity and ecological health. A broad-scale social-ecological analysis supports the finding that the natural feedback between social and ecological elements is broken and recovery efforts are more an attempt at resuscitating the river system to maintain a semblance of historic levels of fish populations and aquatic processes. Adaptive management pathways for the future need to address and build pathways to transformability into recovery planning to achieve resilience for the river system.

Energy projects have the potential to provide critical services for human well-being and help eradicate poverty. However, too many projects fail because their approach oversimplifies the problem to energy poverty: viewing it as a narrow problem of access to energy services and technologies. This thesis presents an alternative paradigm for energy project development, grounded in theories of socio-energy systems, recognizing that energy and poverty coexist as a social, economic, and technological problem.

First, it shows that social, economic, and energy insecurity creates a complex energy-poverty nexus, undermining equitable, fair, and sustainable energy futures in marginalized communities. Indirect and access-based measures of energy poverty are a mismatch for the complexity of the energy-poverty nexus. The thesis, using the concept of social value of energy, develops a methodology for systematically mapping benefits, burdens and externalities of the energy system, illustrated using empirical investigations in communities in Nepal, India, Brazil, and Philippines. The thesis argues that key determinants of the energy-poverty nexus are the functional and economic capabilities of users, stressors and resulting thresholds of capabilities characterizing the energy and poverty relationship. It proposes ‘energy thriving’ as an alternative standard for evaluating project outcomes, requiring energy systems to not only remedy human well-being deficits but create enabling conditions for discovering higher forms of well-being.

Second, a novel, experimental approach to sustainability interventions is developed, to improve the outcomes of energy projects. The thesis presents results from a test bed for community sustainability interventions established in the village of Rio Claro in Brazil, to test innovative project design strategies and develop a primer for co-producing sustainable solutions. The Sustainable Rio Claro 2020 initiative served as a longitudinal experiment in participatory collective action for sustainable futures.

Finally, results are discussed from a collaborative project with grassroots practitioners to understand the energy-poverty nexus, map the social value of energy and develop energy thriving solutions. Partnering with local private and non-profit organizations in Uganda, Bolivia, Nepal and Philippines, the project evaluated and refined methods for designing and implementing innovative energy projects using the theoretical ideas developed in the thesis, subsequently developing a practitioner toolkit for the purpose.

My research is motivated by a rule of thumb that no matter how well a system is designed, some actors fail to fulfill the behavior which is needed to sustain the system. Examples of misbehavior are shirking, rule infraction, and free riding. With a focus on social-ecological systems, this thesis explored the effectiveness of social feedback mechanisms driven by the two available individual options: the exit option is defined as any response to escape from an objectionable state of affairs; and the voice option as any attempt to stay put and improve the state. Using a stylized dynamic model, the first study investigates how the coexistence of participatory and groundwater market institutions affects government-managed irrigation systems. My findings suggest that patterns of bureaucratic reactions to exit (using private tubewells) and voice (putting pressure on irrigation bureaus) are critical to shaping system dynamics. I also found that the silence option – neither exit nor voice – can impede a further improvement in public infrastructure, but in some cases, can improve public infrastructure dramatically. Using a qualitative comparative analysis of 30 self-governing fishing groups in South Korea, the second study examines how resource mobility, group size, and Ostrom’s Design Principles for rule enforcement can co-determine the effectiveness of the voice option in self-controlling rule infractions. Results suggest that the informal mechanism for conflict resolution is a necessary condition for successful self-governance of local fisheries and that even if rules for monitoring and graduated sanctions are not in use, groups can be successful when they harvest only stationary resources. Using an agent-based model of public good provision, the third study explores under what socioeconomic conditions the exit option – neither producing nor consuming collective benefits – can work effectively to enhance levels of cooperation. The model results suggest that the exit option contributes to the spread of cooperators in mid- and large-size groups at the moderate level of exit payoff, given that group interaction occurs to increase the number of cooperators.

This dissertation seeks to understand and study the process of attention harvesting and knowledge production on typical online Q&A communities. Goals of this study include quantifying the attention harvesting and online knowledge, damping the effect of competition for attention on knowledge production, and examining the diversity of user behaviors on question answering. Project 1 starts with a simplistic discrete time model on a scale-free network and provides the method to measure the attention harvested. Further, project 1 highlights the effect of distractions on harvesting productive attention and in the end concludes which factors are influential and sensitive to the attention harvesting. The main finding is the critical condition to optimize the attention harvesting on the network by reducing network connection. Project 2 extends the scope of the study to quantify the value and quality of knowledge, focusing on the question answering dynamics. This part of research models how attention was distributed under typical answering strategies on a virtual online Q&A community. The final result provides an approach to measure the efficiency of attention transferred into value production and observes the contribution of different scenarios under various computed metrics. Project 3 is an advanced study on the foundation of the virtual question answering community from project 2. With highlights of different user behavioral preferences, algorithm stochastically simulates individual decisions and behavior. Results from sensitivity analysis on different mixtures of user groups gives insight of nonlinear dynamics for the objectives of success. Simulation finding shows reputation rewarding mechanism on Stack Overflow shapes the crowd mixture of behavior to be successful. In addition, project proposed an attention allocation scenario of question answering to improve the success metrics when coupling with a particular selection strategy.

This thesis consists of three projects employing complexity economics methods to explore firm dynamics. The first is the Firm Ecosystem Model, which addresses the institutional conditions of capital access and entrenched competitive advantage. Larger firms will be more competitive than smaller firms due to efficiencies of scale, but the persistence of larger firms is also supported institutionally through mechanisms such as tax policy, capital access mechanisms and industry-favorable legislation. At the same time, evidence suggests that small firms innovate more than larger firms, and an aggressive firm-as-value perspective incentivizes early investment in new firms in an attempt to capture that value. The Ecological Firm Model explores the effects of the differences in innovation and investment patterns and persistence rates between large and small firms.

The second project is the Structural Inertia Model, which is intended to build theory around why larger firms may be less successful in capturing new marketshare than smaller firms, as well as to advance fitness landscape methods. The model explores the possibility that firms with larger scopes may be less effective in mitigating the costs of cooperation because conditions may arise that cause intrafirm conflicts. The model is implemented on structured fitness landscapes derived using the maximal order of interaction (NM) formulation and described using local optima networks (LONs), thus integrating these novel techniques.

Finally, firm dynamics can serve as a proxy for the ease at which people can voluntarily enter into the legal cooperative agreements that constitute firms. The third project, the Emergent Firm model, is an exploration of how this dynamic of voluntary association may be affected by differing capital institutions, and explores the macroeconomic implications of the economies that emerge out of the various resulting firm populations.

Sustainability depends in part on our capacity to resolve dilemmas of the commons in Coupled Infrastructure Systems (CIS). Thus, we need to know more about how to incentivize individuals to take collective action to manage shared resources. Moreover, given that we will experience new and more extreme weather events due to climate change, we need to learn how to increase the robustness of CIS to those shocks. This dissertation studies irrigation systems to contribute to the development of an empirically based theory of commons governance for robust systems. I first studied the eight institutional design principles (DPs) for long enduring systems of shared resources that the Nobel Prize winner Elinor Ostrom proposed in 1990. I performed a critical literature review of 64 studies that looked at the institutional configuration of CIS, and based on my findings I propose some modifications of their definitions and application in research and policy making. I then studied how the revisited design principles, when analyzed conjointly with biophysical and ethnographic characteristics of CISs, perform to avoid over-appropriation, poverty and critical conflicts among users of an irrigation system. After carrying out a meta-analysis of 28 cases around the world, I found that particular combinations of those variables related to population size, countries corruption, the condition of water storage, monitoring of users behavior, and involving users in the decision making process for the commons governance, were sufficient to obtain the desired outcomes. The two last studies were based on the Peruvian Piura Basin, a CIS that has been exposed to environmental shocks for decades. I used secondary and primary data to carry out a longitudinal study using as guidance the robustness framework, and different hypothesis from prominent collapse theories to draw potential explanations. I then developed a dynamic model that shows how at the current situation it is more effective to invest in rules enforcement than in the improvement of the physical infrastructure (e.g. reservoir). Finally, I explored different strategies to increase the robustness of the system, through enabling collective action in the Basin.

This dissertation will look at large scale collaboration through the lens of online communities to answer questions about what makes a collaboration persist. Results address how collaborations attract contributions, behaviors that could give rise to patterns seen in the data, and the properties of collaborations that drive those behaviors.

It is understood that collaborations, online and otherwise, must retain users to remain productive. However, before users can be retained they must be recruited. In the first project, a few necessary properties of the ``attraction'' function are identified by constraining the dynamics of an ODE (Ordinary Differential Equation) model. Additionally, more than 100 communities of the Stack Exchange networks are parameterized and their distributions reported.

Collaborations do not exist in a vacuum, they compete with and share users with other collaborations. To address this, the second project focuses on an agent-based model (ABM) of a community of online collaborations using a mechanistic approach. The ABM is compared to data obtained from the Stack Exchange network and produces similar distributional patterns.

The third project is a thorough sensitivity analysis of the model created in the second project. A variance based sensitivity analysis is performed to evaluate the relative importance of 21 parameters of the model. Results indicate that population parameters impact many outcome metrics, though even those parameters that tend towards a low impact can be crucial for some outcomes.

The South African Middle Stone Age (MSA), spanning the Middle to Late Pleistocene (Marine Isotope Stages (MIS) 8-3) witnessed major climatic and environmental change and dramatic change in forager technological organization including lithic raw material selection. Homo sapiens emerged during the MSA and had to make decisions about how to organize technology to cope with environmental stressors, including lithic raw material selection, which can effect tool production and application, and mobility.

This project studied the role and importance of lithic raw materials in the technological organization of foragers by focusing on why lithic raw material selection sometimes changed when the behavioral and environmental context changed. The study used the Pinnacle Point (PP) MSA record (MIS6-3) in the Mossel Bay region, South Africa as the test case. In this region, quartzite and silcrete with dramatically different properties were the two most frequently exploited raw materials, and their relative abundances change significantly through time. Several explanations intertwined with major research questions over the origins of modern humans have been proposed for this change.

Two alternative lithic raw material procurement models were considered. The first, a computational model termed the Opportunistic Acquisition Model, posits that archaeological lithic raw material frequencies are due to opportunistic encounters during random walk. The second, an analytical model termed the Active-Choice Model drawn from the principles of Optimal Foraging Theory, posits that given a choice, individuals will choose the most cost effective means of producing durable cutting tools in their environment and will strategically select those raw materials.

An evaluation of the competing models found that lithic raw material selection was a strategic behavior in the PP record. In MIS6 and MIS5, the selection of quartzite was driven by travel and search cost, while during the MIS4, the joint selection of quartzite and silcrete was facilitated by a mobility strategy that focused on longer or more frequent stays at PP coupled with place provisioning. Further, the result suggests that specific raw materials and technology were relied on to obtain food resources and perform processing tasks suggesting knowledge about raw material properties and suitability for tasks.

A key factor in the success of social animals is their organization of work. Mathematical models have been instrumental in unraveling how simple, individual-based rules can generate collective patterns via self-organization. However, existing models offer limited insights into how these patterns are shaped by behavioral differences within groups, in part because they focus on analyzing specific rules rather than general mechanisms that can explain behavior at the individual-level. My work argues for a more principled approach that focuses on the question of how individuals make decisions in costly environments.

In Chapters 2 and 3, I demonstrate how this approach provides novel insights into factors that shape the flexibility and robustness of task organization in harvester ant colonies (Pogonomyrmex barbatus). My results show that the degree to which colonies can respond to work in fluctuating environments depends on how individuals weigh the costs of activity and update their behavior in response to social information. In Chapter 4, I introduce a mathematical framework to study the emergence of collective organization in heterogenous groups. My approach, which is based on the theory of multi-agent systems, focuses on myopic agents whose behavior emerges out of an independent valuation of alternative choices in a given work environment. The product of this dynamic is an equilibrium organization in which agents perform different tasks (or abstain from work) with an analytically defined set of threshold probabilities. The framework is minimally developed, but can be extended to include other factors known to affect task decisions including individual experience and social facilitation. This research contributes a novel approach to developing (and analyzing) models of task organization that can be applied in a broader range of contexts where animals cooperate.