Marco A. Janssen

Studying social-ecological systems, in which agents interact with each other and their environment are important both for sustainability applications and for understanding how human cognition functions in context. In such systems, the environment shapes the agents’ experience and actions, and in turn collective action of agents changes social and physical aspects of the environment. Here we review current investigation approaches, which rely on a lean design, with discrete actions and outcomes and little scope for varying environmental parameters and cognitive demands. We then introduce a multiagent reinforcement learning (MARL) approach, which builds on modern artificial intelligence techniques, and provides new avenues to model complex social worlds, while preserving more of their characteristics, and allowing them to capture a variety of social phenomena. These techniques can be fed back to the laboratory where they make it easier to design experiments in complex social situations without compromising their tractability for computational modeling. We showcase the potential MARL by discussing several recent studies that have used it, detailing the way environmental settings and cognitive constraints can lead to the emergence of complex cooperation strategies. This novel approach can help researchers bring together insights from human cognition, sustainability, and AI, to tackle real world problems of social-ecological systems.

When people use shared resources, overextraction can occur. While deliberation tends to mitigate shared resource exploitation problems, the question remains: under what conditions does group chat improve cooperation in shared resource dilemmas? This study analyzes chat and game data from about 1500 rounds of gameplay involving 143 groups across 4 resource types using Sentiment Analysis and Structural Topic Model. We find that, despite their fundamental differences, the 4 games tend to have similar discussions, including strategizing actions, coordinating choices, and socialization, but they differ in which topics explain cooperation within each game. Discussion topics promoting cooperation include coordination in the foraging game (FOR) and long-term goals in the groundwater game (GG). However, discussion topics negatively associated with cooperation include off-topic/socialization in FOR and the irrigation game (IRR) and crop choice affirmation in GG. We suggest that the context in which communication occurs matters, and biophysical characteristics, rules of the game, and levels of uncertainty explain some variations of our findings.

Achieving more sustainable adaptation to social–environmental change demands the transformation of the narratives that provide the rationale for risk governance. These narratives often reflect long-standing beliefs about social and political relationships, ascribe actions and responsibilities, and specify solutions to risk. When such solutions are implemented through material investments in landscapes, these narratives become embedded in physical infrastructure with long legacies. Dominant narratives can mask a range of divergent problem framings. By masking alternatives, narratives can contribute to the persistence of unsustainable governance trajectories. Decision-support tools have begun to represent narratives as drivers of system dynamics; making narratives visible can reveal opportunities for more sustainable governance. We present the results of the project “The Dynamics of Multi-Scalar Adaptation in the Megalopolis”, a dynamic, exploratory model of socio-hydrological risks in Mexico City that was designed to both endogenize and simultaneously challenge the dominant narratives that characterize water-risk governance in the city. Qualitative data characterize dominant narratives at city and borough scales. An agent-based model, informed by multicriteria decision analysis and coupled with hydrological, urbanization, and climatic model inputs, permitted the development of exploratory governance scenarios designed to challenge dominant narratives. Scenarios revealed how dominant narratives may contribute to the persistence of vulnerability “hotspots” in the city, despite stated goals of equity and vulnerability alleviation. Participatory workshops with representatives of the city government illustrate how making such narratives visible through exploratory modeling can lead to a questioning of prior assumptions and causal relations, recognition of a need for intersectoral collaboration, and insights into potential management strategies.

Rule enforcement is critical in democratic, self-governing societies. Many political disputes occur when citizens do not understand the fundamental rationales for enforcement (e.g., COVID-19 pandemic). We examined how naïve groups learn and develop wise enforcement systems. Based on theories from behavioral economics, political science, psychology, and education, we predicted that groups need to experience failure of an enforcement system, but be guided on restorative justice principles to collectively learn from this failure. Undergraduate students (N = 288) from a Midwestern U.S. metropolitan university self-governed a simulated common-pool resource with real financial payoffs. Groups began with one of three conditions designed to create different experiences with enforcement and regulatory failure: (a) no enforcement (no communication or peer sanctioning), (b) lax enforcement (communication with peer-sanctioning), or (c) regulatory abuse (peer sanctioning without communication). Half then received facilitated guidance on restorative justice principles (e.g., discuss whether/why to use sanctions). To examine cooperation, we measured how well participants maintained the resource. To examine group learning, we created a novel coding system, which tracked groups’ constitutional decisions about conservation agreements and enforcement, conceptual understanding, and the enforcement systems they created. The no-enforcement and lax-enforcement conditions quickly yielded moderate cooperation via voluntary agreements. However, such agreements prevented groups from discovering how and why to use enforcement (peer sanctioning) to improve performance. Initial exposure to regulatory failure had different effects depending on facilitation. Unfacilitated groups fixated on initial misconceptions, causing them to abandon or create less sophisticated enforcement systems, hindering cooperation. Facilitated groups learned from prior failure—discovering principles of wise enforcement (e.g., collective efficiency, self-restraint)—and created more sophisticated enforcement systems (e.g., coordinated sanctions) that improved cooperation. Guidance on restorative justice principles and experience with regulatory abuse may be necessary preconditions for naïve individuals to understand and develop wiser collective enforcement systems.

There is limited research about how groups solve collective action problems in uncertain environments, especially if groups are confronted with unknown unknowns. We aim to develop a more comprehensive view of the characteristics that allow both groups and individuals to navigate such issues more effectively. In this article, we present the results of a new online experiment where individuals make decisions of whether to contribute to the group or pursue self-interest in an environment with high uncertainty, including unknown unknowns. The behavioral game, Port of Mars is framed as a first-generation habitat on Mars where participants have to make decisions on how much to invest in the shared infrastructure to maintain system health and how much to invest in personal goals. Participants can chat during the game, and take surveys before and after the game in order to measure personality attributes and observations from the game. Initial results suggest that a higher average social value orientation and more communication are the key factors that explain why some groups are more successful than others in surviving Port of Mars. Neither other attributes of players nor the group’s communication content explain the observed differences between groups.

Contemporary business process modeling is based on predefined constraints where flexibility is built in. Current business challenges result from an increase in data which, are a valuable source for decision taking. Control models from cybernetics could do the job, especially when learning capabilities are added. However, in an agent-based architecture there is something to add: the social component. This position paper aims to advance understanding and practical application of how organizations can effectively utilize the abundance of data in their operational processes while also exploring novel approaches to organizational dynamics and coordination. More in detail, the paper outlines a model that combines socialComplex Responsive Processes (CRP) with a cyber-physical control cycle within a multi-agent simulated business process.

Combating environmental degradation requires global cooperation. We here argue that institutional designs for such efforts need to account for human behavior. The voyage of the Titanic serves as an analogous case to learn from, and we use behavioral insights to identify critical aspects of human behavior that serve as barriers or opportunities for addressing the challenges we face. We identify a set of public goods that may help us mitigate identified negative aspects of human behavior, while leveraging the positive aspects: standards and best practices, mechanisms for large-scale coordination, and curation of information to raise awareness and promote action. We use existing international organizations, providing at least one of these capacities, as cases to learn from before applying our insights to existing institutional solutions for global environmental protection. We identify institutional design features that, if adapted to better account for human behavior, could lead to more effective institutional solutions.

The rapid expansion of human activities in outer space is likely to bring new economic, social, and political dilemmas in the next 50 to 100 years. Future governance will have to increasingly juggle earth-space social justice, resource trade-offs, and environmental sustainability issues. This poses new challenges to the governance of global commons, i.e. whether existing studies are fit to address commons in a global context and whether the governance of outer space commons (dis)integrates with Earth-bound sustainability governance. To explore these questions, this study uses scenario-building techniques to generate alternative future scenarios via a workshop conducted during the 2022 Commons in Space conference. We derived four future scenarios based on two major contextual conditions: (i) the degree of equity in resource distribution in space, and (ii) the degree of integration with Earth-bound sustainability, more specifically Earth system governance. The four alternative scenarios are (i) Space Cartel in which the use of space resources becomes dominated by the rich and powerful; (ii) Earth-centric Gold Rush in which the current ‘business as usual’ continues; (iii) Open Space (also Space Utopia) in which open access of space resources leads to thriving developments in space at the expense of sustainability on Earth; and finally, (iv) Earth-Space Sustainability in which challenges on Earth and in space are addressed through an integrative governance model. Based on the challenges identified from these scenarios, we discuss specific as well as cross-cutting implications for policy and governance to better address commons in space in the future.

Adapting to social and environmental change requires learning and governance that span ecological levels, political jurisdictions, and management challenges. Governance of these challenges is often comprised of public and private sector actors with overlapping jurisdictions that work together—termed polycentric governance. Polycentric governance systems have been found to improve adaptability through learning. In this paper, we compare how local organizations perceive a governance systems’ function and structure to help them learn and adapt to change. In our interviews with organization leaders in three north-central US states, we used expert elicitation to compare the degree to which the organizations’ partners help them experiment and learn to adapt to challenges. The challenges most frequently identified included social challenges like sharing knowledge and funding as well as ecological issues related to the resource. The associated polycentric governance systems’ structures varied by state. Independence and jurisdictional overlap—measures of polycentricity—differed by partner type, while consideration of partners’ best practices was similar for all partner types. Most partners were said to provide helpful information and respond to queries facilitating learning, but government partners were not always encouraging innovation or flexible implying less space for experimentation. We found that in each of the three states there is a mixture of actors at multiple scales partnering with the lake organizations at different frequencies and modes of interaction. We conclude that polycentric governance is beneficial for learning and experimentation, and that different structures may be beneficial to adapting within different contexts or problems definitions. The challenge for these systems is controlling areas of risk while providing flexibility to experiment and adapt to changing conditions.

Unreliable public water supplies cause human hardships and are still common worldwide. Households often deal with the issue by adopting various coping strategies that are representative of economic decentralization (e.g., using private wells, sourcing from third-party vendors) and political decentralization (e.g., making petitions to a public provider). There is growing interest in these user-level decentralized coping strategies, but their relative effects on provider’s behavior and the long-term sustainability of public water supply remain unclear. This puzzle has not been tackled using an experimental approach. This study reports a controlled behavioral experiment conducted to test the relative effectiveness of different coping strategies on infrastructure quality and users-provider cooperation in the context of agricultural water supply. We tested experimental treatments involving two classes of coping strategies: exit and voice. The exit option represents users’ shift to an alternative water source. The voice option represents users’ direct effort to influence a public irrigation service provider. We recruited 272 human subjects into our 4-player experiment (one provider and three users) and observed and compared their decisions under four treatments (exit, voice, their combination, and no options). The results show that the voice option leads to improved outcomes compared to other choices that include the exit option, suggesting that contrary to previously thought, the exit option can be detrimental to users-provider cooperation. We also observed that a user tends to cooperate more (pay and use the public service) when other users do the same.

Governance of shared resources needs to overcome collective action problems. Relational values and decision-making play a critical role in this process. Approaches are needed to stimulate self-governance, taking relational values into account. We review the literature on the use of collective action games as a tool to stimulate social learning and self-governance. We emphasize the importance of legitimacy in decision-making and the risk of crowding out internalized motivations — for instance, based on relational values — with instrumental incentive mechanisms. We further highlight the need to include ecological outcome indicators in the game design to allow the activation of relational values. Our review concludes that games used as part of a set of participatory activities enable communities to come together to identify relevant problems and craft potential solutions.

Framed field experiments (experimental games) are widely used to assess factors affecting cooperation in management of the commons. However, there is relatively little attention to how details of the games affect experimental results. This paper presents qualitative and quantitative results from a framed field experiment in which participants make decisions about extraction of a common-pool resource, a community forest. The experiment was conducted in 2017–2018 with 120 groups of resource users (split by gender) from 60 habitations in two Indian states, Andhra Pradesh and Rajasthan. We test whether within-subject treatments (non-communication, communication, and optional election of institutional arrangements (rules)), remuneration methods, and design of the game board affect harvest behavior and groups’ tendency to cooperate. We also examine how characteristics of the community and players affect players’ choices in the game, with special attention to gender differences. Results reveal participants harvested substantially less than the Nash prediction even in the absence of communication, with men extracting less than women in both states. For male groups in both states, both communication and optional rule election were associated with lower group harvest per round, as compared to the reference non-communication game. For female groups in both states communication itself did not significantly slow resource depletion; but introduction of optional rule election did reduce harvest amounts. For both men and women in Andhra Pradesh and men in Rajasthan, incentivized payments to individual participants significantly lowered group harvest, relative to community flat payment, suggesting such payments stimulated deliberation among game players. Findings have methodological and practical implications for designing behavioral intervention programs to improve common-pool resource governance.

Context

Network-theoretic tools contribute to understanding real-world system dynamics, such as species survival or spread. Network visualization helps illustrate structural heterogeneity, but details about heterogeneity are lost when summarizing networks with a single mean-style measure. Researchers have indicated that a system composed of multiple metrics may be a more useful determinant of structure, but a formal method for grouping metrics is still lacking.

Objectives

Our objective is to present a tool that can account for multiple properties of network structure, which can be related to model outcomes.

Methods

We develop an approach using the statistical concept of moments and systematically test the hypothesis that this system of metrics is sufficient to explain variation in processes that take place on networks, using an ecological system as an example.

Results

Our results indicate that the moments approach outperforms single summary metrics by adjusted-R² and AIC model fit criteria, and accounts for a majority of the variation in process outcomes.

Conclusions

Our scheme is helpful for indicating when additional structural information is needed to describe system process outcomes such as survival or spread.

An agent-based model is presented that aims to capture the involvement of inequality and trust in collective action in a classic commons dilemma before, during, and after communication. The model assumptions are based on the behavioral theory of collective action of Elinor Ostrom and the ‘humanistic rational choice theory’. The commons dilemma is represented as a spatially explicit renewable resource. Agent’s trust in others has an impact on the harvesting of shared resources, and trust is influenced by observed harvesting behavior and cheap talk. We calibrated the model using data from a prior set of lab experiments on inequality, trust, and communication. The best fit to the data consists of a population with a small share of altruistic and selfish agents and a majority of conditional cooperative agents sensitive to inequality and who would cooperate if others did. Communication increased trust explaining the better group performance when communication was introduced. The modeling results complement prior communication research and clarify the dynamics of reciprocal cooperation commonly observed in robust resource governance systems.

It is puzzling how altruistic punishment of defectors can evolve in large groups of nonrelatives, since punishers should voluntarily bear individual costs of punishing to benefit those who do not pay the costs. Although two distinct mechanisms have been proposed to explain the puzzle, namely voluntary participation and group-level competition and selection, insights into their joint effects have been less clear. Here we investigated what could be combined effects of these two mechanisms on the evolution of altruistic punishment and how these effects can vary with nonparticipants’ individual payoff and group size. We modelled altruistic punishers as those who contribute to a public good and impose a fine on each defector, i.e., they are neither pure punishers nor excluders. Our simulation results show that voluntary participation has negative effects on the evolution of cooperation in small groups regardless of nonparticipants’ payoffs, while in large groups it has positive effects within only a limited range of nonparticipants’ payoff. We discuss that such asymmetric effects could be explained by evolutionary forces emerging from voluntary participation. Lastly, we suggest that insights from social science disciplines studying the exit option could enrich voluntary participation models.

Complex Responsive Processes (CRP) focus on the interaction between agents, where they exchange knowledge, opinions, experience, and values. In decentralized decision making, this could accelerate the monitoring, analysis, planning and execution process, as defined in a control mechanism like MAPE-K. For Multi-Agent Systems with a decentralized or hybrid architecture the gesture (e.g., agent expression) and response dynamics of complex responsive interaction could be valuable to reduce the entropy of a system. Until today, the CRP mechanisms have not been formalized in Multi-Agent decentralized decision making as it lacks a formal model to express inter-agent dialectics. This position paper discloses the area where an extension of the MAPE-K control cycle can be made to include the formalized CRP processes. This extension consists of a set of methods that include the responsive processes of multiple agents and will be used to update the Knowledge base in the MAPE-K model.

The U.S. highway system is an iconic example of civil infrastructure. Yet it also exemplifies the challenges of infrastructure sustainability. The American Society for Civil Engineers gave the American road infrastructure a grade of “D” since the roads “are often crowded, frequently in poor condition, chronically underfunded, and are becoming more dangerous.” In this paper, we seek to understand the intertwined social and technical processes that lead to this unsustainability by examining the U.S. highway system from the perspective of coupled infrastructure systems (CIS), a transdisciplinary framework that aims to analyze governance challenges of shared resources from a dynamic systems perspective. We use highways as a special example of the broader challenge of providing and maintaining the shared infrastructure of all types. Our analysis of historical data concludes that the unsustainability of highways as coupled infrastructure systems can be explained from dysfunctional information feedbacks.

Will you be able to run your computational models in the future? Even with well-documented code, this can be difficult due to changes in the software frameworks and operating systems that your code was built on. In this paper we discuss the use of containers to preserve code and their software dependencies to reproduce simulation results in the future. Containers are standalone lightweight packages of the original model software and their dependencies that can be run independent of the platform. As such they are suitable for reuse and sharing results. However, the use of containers is rare in the field of modeling social-environmental systems. We provide an introduction to the basic principles of containerization, argue why it would be beneficial if this tool became common practice in the field, describe a conceptual walkthrough to the process of containerizing a model, and reflect on near future directions of containerization workflows.

Institutional structures can fundamentally shape opportunities for adaptive governance of water resources at multiple ecological and societal scales. The properties of adaptive governance have been widely examined in the literature. However, there has been limited focus on how institutions can promote or hinder the emergence of adaptive governance. Elinor Ostrom’s institutional theory stresses the importance of formal and informal norms and rules in effective governance of natural resources. Specifically, Ostrom’s “design principles” (DPs) are considered important because they increase the capacity for adaptive decision making and facilitate the emergence of self-organization at smaller scales. Self-organizing agents can frequently modify rules-in-use, procedures, and technical methods to tackle changing ecological conditions and address significant management issues left by more traditional governments. In this study, we examine institutional arrangements for successful water governance by analyzing (1) the co-occurrence of DPs in irrigation systems, and (2) the combination(s) of DPs leading to social and ecological success. We collaborated with a local non-profit organization to review institutional records and conduct interviews in 50 irrigation communities in Andhra Pradesh and Karnataka in South India. Using qualitative comparative analysis, we found that the effectiveness of design principles is contingent on biophysical properties, such as the size of the watershed being governed, and attributes of the community, such as population size. We also discuss the methodological and data-related challenges involved in collecting primary data for conducting a context-specific institutional analysis. Our study offers a much-needed example of empirical research that investigates the role of operational level rules in adaptive water governance.

The extent to which employees change jobs, known as the job mobility rate, has been steadily declining in the US for decades. This decline is understood to have a negative impact on both productivity and wages, and econometric studies fail to support any single cause brought forward. This decline coincides with decreases in household savings, increases in household debt, and wage stagnation. We propose that the decline could be the consequence of a complex interaction between mobility, savings, wages, and debt, such that if changing jobs incur costs that are paid out of savings or incurs debt in the absence of sufficient savings, a negative feedback loop is generated. People are further restricted in making moves by their debt obligations and inability to save, which in turn depresses wages further. To explore this hypothesis, we developed a stylized model in which agents chose their employment situation based on their opportunities and preferences for work and where there are costs to changing jobs and the possibility of borrowing to meet those costs. We indeed found evidence of a negative feedback loop involving changes, wages, savings, and debt, as well as evidence that this dynamic results in a level of wealth inequality on the same scale as we see today in the US.

This study argues that scholars and policy-makers need to understand environmental activists better to bridge the gap between growing activism and policy. Conventional wisdom is that environmental activists generally support stronger climate policies. But there is still little understanding about diversity of views within activist groups when it comes to specific policies, and existing studies indicate that their views are not uniform, which can weaken their impact as a group. Activists might unite to demand change, but not necessarily agree on details of the desired change. Exploring the differences within the group, this paper focuses on how to nudge those who already share favorable attitudes towards policies that mitigate climate change. The motivation has been to see, in presence of general support for stronger environmental policies, whether this support could be channeled into more specific policies. We first take on a methodological challenge to construct an index of environmental predisposition. Then drawing from existing social-behavioral scholarship, we analyze results of an experimental survey with select treatments previously reported as promising. In November and December 2019, we collected responses from 119 participants at the Fridays for Future demonstrations in Germany. The results indicate that there are indeed important differences within the group, and nudging effects exist even in this rather strongly predisposed group, with participants assigned to the experimental group showing higher levels of support for the introduction of a carbon tax that is traditionally seen as a difficult policy to gain widespread public support. We find that those who score neither too high nor too low are more likely to respond to nudging. Yet, the effects vary for general outcomes such as policy support, behavioral intentions, and environmental citizenship. Overall, the findings show the value of understanding the heterogeneity of individual views within environmental movements better and directing interventions in large resource systems such as climate to specific issues and target groups for accelerating transformations towards sustainability.

Conventional wisdom (rational choice theory) assumes that individuals are destined to collectively destroy vital ecological systems due to their narrow self-interest. In contrast, Humanistic Rational Choice Theory (HRCT) assumes individuals can cooperatively self-govern, devising effective conservation agreements and governance systems to constrain self-interest for mutual benefit. To test this assumption, we examined the motivational, perceptual, and cooperative outcomes of communication in a resource dilemma experiment. HRCT assumes that poorly managed dilemmas undermine people’s fundamental needs (e.g., procedural justice, security, equity), motivating them to self-govern. Groups that make decisions fairly (e.g., democratically) and enforce their agreements, should satisfy their collective needs better, ensuring better institutional acceptance and trust, thereby improving cooperation and sustainability. Small groups of four (N = 41 groups) harvested valuable resources from a shared pool without communication (Phase 1), with communication (Phase 2), and then without communication (Phase 3). Groups destroyed the resource and reported low need satisfaction during Phase 1. During Phase 2, most groups created governance systems, greatly improving their need satisfaction (ds≥1.32), trust (d = 2.30), cooperation and resource sustainability (η²=0.87). Democratically governed groups reported the greatest need satisfaction, intrinsic motivation (i.e., institutional internalization and acceptance), and trust, especially if they primarily used positive social sanctions (e.g., praise) to enforce their agreements. Negative sanctions (e.g., shaming, threats) backfired, unless used in democratic groups. These factors accounted for 47% of the variance in Phase 3 voluntary cooperation and resource sustainability. Groups self-governed to collectively satisfy their interdependent fundamental needs.

Chapter 21 focuses on controlled behavioural experiments, methods that randomly divide participants into different groups (treatments), controlling conditions across these treatments and allowing only the variable of interest to vary. Controlled behavioural experiments are used to test the conditions under which we can expect collective action to emerge. The chapter discusses controlled behavioural experiments in the form of common-pool resource games and public good games. It goes on to discuss the types of social-ecological systems (SES) problems and research questions commonly addressed by this set of methods, as well as their limitations, resource implications and new emerging research directions. The chapter also includes an in-depth case study showcasing the application of controlled behavioural experiments, and suggested further readings on these methods.

Faced with mounting resistance against mining, neoliberal governance resorts to polarising strategies that delegitimise the heterogenous positions people hold regarding mining. In this paper, we contrast and complicate these dichotomies with the lived experiences on the ground in Kyrgyzstan. We focus on the ‘Taldy-Bulak Levoberezhny’ gold mine near the town of Orlovka that has been lauded by the state and business community as a paragon of company-community ‘cooperation’. We question how the gold mine has come to be an exemplary case of cooperation in a conflict-rife sector. Based on behavioural experiments, surveys, and in-depth inquiry, we follow and unpack entanglements of valuations, discourses and practices that have repackaged Orlovka from a former Soviet mining town in depression into a putative model of progress. Our interdisciplinary account unravels the contradictory processes of re/making extractive frontiers and managing resistance to extractivist expansion that interweave neoliberal practices with nationalist discourses. Beneath the discourses praising Orlovka, we find a community that has never stopped resisting despite consenting to the gold mine. The extractive entanglements we unearth exemplify the diversity of exigencies and aspirations behind resisting, negotiating and/or allowing mining while attesting to the diversified portfolio of tactics that silence and delegitimise these life concerns.

How do the social and ecological attributes of social-ecological systems enable outcomes of those systems? The high concentration of lake organizations in northern USA enables us to study social, institutional, and ecological attributes that correlate with performance of common pool resource governance—institutional fit. In the summer of 2019, we performed an in-depth comparative study of thirty-one lake organizations in Vilas County, Wisconsin using data collected through semi-structured interviews, websites, and agency databases. We systematically compared the cases using crisp-set qualitative comparative analysis, specifically analyzing how the eight Ostrom institutional design principles lead to different outcomes for the lake social-ecological systems. The Ostrom institutional design principles played an important role in SES governance outcomes where there was low-resource dependence. We found that different combinations of design principles, social, and ecological conditions led to the same lake SES outcomes—equifinality. Although we expected that there were no panaceas for lake governance, we were surprised by the high diversity in organizational goals and the relative low diversity of rules in use.

Local users may invest in managing common pool resources, thereby promoting social and ecological resilience. Institutional or economic limits on access are regarded as essential preconditions for incentivizing local investments, but we show that investment incentives can exist even under open access. We modeled a recreational harvest fishery in which local or centralized managers invest in fish stocking to maximize social welfare. Although classic open access dissipation of rents occurs at equilibrium, the sluggish response of fishing effort to changing conditions allows welfare to accrue in transition to equilibrium. This transient welfare creates persistent incentives to invest. Empirical observations showed that stocking by local collective action groups occurred at rates similar to model-predicted optima, while centralized stocking occurred at rates greater than predicted optima. Our results emphasize the potential benefits of local involvement in managing the commons, even under conditions that were previously thought to preclude effective collective action.

Informal urban expansion, or conversion of land to urban land uses, outpaces formal urbanization in the developing world. Understanding why this informality exists and persists is essential to counteract characterizations that it is chaotic and ungovernable. This research examines who shapes the informal arrangements developed to meet unmet housing needs that expand the urban footprint, from social housing projects to concentrated squatting in Mexico City metropolis from 2000 to 2016. Institutional analysis elucidates the distribution of payoffs in the “action situation” where decisions about urban land are made, and among “institutional entrepreneurs”, actors that repeatedly evade or alter formal rules or create new rules of urban land regulation. We use interview data regarding the distribution of costs and benefits among 54 actors involved in recent informal urban expansion to provide low- and middle-income housing (2000–2016) to identify potential leverage points for institutional change. We describe four types of informal urban land transactions: i) urbanizing individual plots of land, ii) flipping or subdividing land into multiple parcels, iii) invading land, and iv) manipulating social and public housing developments. We find institutional entrepreneurs—intermediaries, developers, and politicians—disproportionately benefit from and reinforce unplanned urban expansion. These entrepreneurs provide housing for the urban poor, but with social and environmental costs, including exploitation of informal settlers and urbanization of conservation land and loss of environmental services. Disaggregating informality into its component pervasive institutions and analyzing the distribution of payoffs in and beyond Mexico City provides insights about governance for urban sustainability.

What makes Question & Answer (Q&A) communities productive? In this paper, we look into how the diversity of behavioral types of agents impacts the performance of Q&A communities using different performance metrics. We do this by developing an agent-based model informed by insights from previous studies on Q&A communities. By analyzing the different strategies for how questions are selected to answer, we find that there are mixtures of strategies leading to the best outcomes for different performance conditions. Particularly, Q&A communities that encourage participants to focus on answering the new questions reach the best performance in answering the questions, creating the long term value, and improving the competence of solving difficulty. In conclusion, we find that the current strategies of question selection on Stack Overflow are in line with the high performance of producing public benefit from the collective attention available.

Incorporating representations of human decision-making that are based on social science theories into social-ecological models is considered increasingly important – yet choosing and formalising a theory for a particular modelling context remains challenging. Here, we reflect on our experiences of selecting, formalising and documenting psychological and economic theories of human decision-making for inclusion in different agent-based models (ABMs) of natural resource use. We discuss the challenges related to four critical tasks: How to select a theory? How to formalise a theory and how to translate it into code? How to document the formalisation? In this way, we present a systematic overview of the choices researchers face when including theories of human decision-making in their ABMs, reflect on the choices we made in our own modelling projects and provide guidance for those new to the field. Also, we highlight further challenges regarding the parameterisation and analysis of such ABMs and suggest that a systematic overview of how to tackle these challenges contributes to an effective collaboration in interdisciplinary teams addressing socio-ecological dynamics using models.

Being able to replicate research results is the hallmark of science. Replication of research findings using computational models should, in principle, be possible. In this manuscript, we assess code sharing and model documentation practices of 7500 publications about individual-based and agent-based models. The code availability increased over the years, up to 18% in 2018.

Model documentation does not include all the elements that could improve the transparency of the models, such as mathematical equations, flow charts, and pseudocode. We find that articles with equations and flow charts being cited more among other model papers, probably because the model documentation is more transparent.

The practices of code sharing improve slowly over time, partly due to the emergence of more public repositories and archives, and code availability requirements by journals and sponsors. However, a significant change in norms and habits need to happen before computational modeling becomes a reproducible science.

In this study, we discuss Port of Mars, a new experimental design to study collective action problems in extreme environments under conditions of high uncertainty. The game is situated in the first-generation habitat on Mars, providing an engaging narrative for players to navigate collective action problems. This pilot study finds that most groups are able to avoid the collapse of the habitat, and that the existence of thresholds seems to make groups cooperative. The game demonstrates the initial outcomes of a transdisciplinary project that could provide new ways to study commons governance under high uncertainty.

The Palaeo-Agulhas Plain (PAP), when exposed, presented Middle Stone Age (MSA) foragers at Pinnacle Point (PP) on the South Coast of South Africa with new sources of raw materials to make stone tools. Sea-level fluctuations and the changing size of the Paleo-Agulhas Plain throughout the Pleistocene PP record ∼165 ka to 50 ka would have altered the availability of different resources, thus potentially forcing new raw material procurement strategies. The relative frequencies of raw material throughout the PP sequence shows that frequencies of raw material types did change, especially after 90 ka. What caused these changing frequencies is debated and centers on whether targeted procurement of specific raw materials was the cause, or if simple raw material availability and abundance due to the changing environmental context in conjunction with opportunistic procurement drove such shifts. The application of a neutral model of stone raw material procurement presented here evaluates whether random walk in the region surrounding the PP site during different coastline configurations (Marine Isotope Stage 6, 5, and 4) explains the observed shifts in raw material usage. Put differently, did opportunistic acquisition of raw materials during random walk in these different environments cause the observed raw material pattern? Model simulations and a sensitivity analysis provide no convincing evidence that observed raw material frequencies at PP resulted from opportunistic acquisition during random walk.

The Palaeo-Agulhas Plain formed an important habitat exploited by Pleistocene hunter-gatherer populations during periods of lower sea level. This productive, grassy habitat would have supported numerous large-bodied ungulates accessible to a population of skilled hunters with the right hunting technology. It also provided a potentially rich location for plant food collection, and along its shores a coastline that moved with the rise and fall of sea levels. The rich archaeological and paleontological records of Pleistocene sites along the modern Cape south coast of South Africa, which would have overlooked the Palaeo-Agulhas Plain during Pleistocene times of lower sea level, provides a paleoarchive of this extinct ecosystem. In this paper, we present a first order illustration of the “palaeoscape modeling” approach advocated by Marean et al. (2015). We use a resourcescape model created from modern studies of habitat productivity without the Palaeo-Agulhas Plain. This is equivalent to predominant Holocene conditions before recent landscape modifications for farming. We then run an agent-based model of the human foraging system to investigate several research questions. Our agent-based approach uses the theoretical framework of optimal foraging theory to model human foraging decisions designed to optimize the net caloric gains within a complex landscape of spatially and temporally variable resources. We find that during the high sea-levels of MIS 5e (+5–6 m asl) and the Holocene, the absence of the Plain left a relatively poor food base supporting a much smaller population relying heavily on edible plant resources from the current Cape flora. Despite high species diversity of plants with edible storage organs, and marine invertebrates, encounter rates with highly profitable resources were low. We demonstrate that without the Palaeo-Agulhas Plain, human populations must have been small and low-density, and exploited plant, mammal, and marine resources with relatively low caloric returns. The exposure and contraction of the Palaeo-Agulhas Plain was likely the single biggest driver of behavioural change during periods of climate change through the Pleistocene and into the transition to the Holocene.

Two social feedbacks critical for redressing decline in organizational performance are exit (changing membership to a better performing organization) and voice (members’ expression of discontent). In self-governing organizations of common-pool resources (CPRs) experiencing decline from poor rule conformance, the exit option is often unavailable due to a closed membership policy. Thus, members should rely on the voice option to reverse the trend. However, it is poorly understood under what set of conditions members can successfully use the voice option to govern their CPRs. We analyzed 30 self-governing fishing groups in South Korea to generate configurations of institutional and social-ecological conditions linked to the successful voice option. We considered Ostrom’s Design Principles for rule enforcement as institutional conditions and resource mobility and group size as social-ecological factors affecting institutional fit. We find that if the informal mechanism for conflict resolution is absent, fishing groups will be unsuccessful; even if rules for monitoring and graduated sanctions are not in use, groups can be successful when they harvest only stationary resources and the informal conflict-resolution is present; and groups managing mobile resources need graduated sanctions to be successful, while those appropriating only stationary resources can achieve the same outcome without such sanctions.

Tipping point dynamics are fundamental drivers for sustainable transition pathways of social-ecological systems (SES). Current research predominantly analyzes how crossing tipping points causes regime shifts, however, the analysis of potential transition pathways from these social and ecological tipping points is often overlooked. In this paper, we analyze transition pathways and the potential outcomes that these may lead to via a stylized model of a system composed of interacting agents exploiting resources and, by extension, the overall ecosystem. Interactions between the social and the ecological system are based on a perception-exploitation framework. We show that the presence of tipping points in SES may yield counter-intuitive social-ecological transition pathways. For example, the high perception of an alarming ecological state among agents can provide short-term ecological benefits, but can be less effective in the long term, compared to a low-perception condition. This work also highlights how understanding non-linear interactions is critical for defining suitable transition pathways of any SES.

Modeling is essential to characterize and explore complex societal and environmental issues in systematic and collaborative ways. Socio-environmental systems (SES) modeling integrates knowledge and perspectives into conceptual and computational tools that explicitly recognize how human decisions affect the environment. Depending on the modeling purpose, many SES modelers also realize that involvement of stakeholders and experts is fundamental to support social learning and decision-making processes for achieving improved environmental and social outcomes. The contribution of this paper lies in identifying and formulating grand challenges that need to be overcome to accelerate the development and adaptation of SES modeling. Eight challenges are delineated: bridging epistemologies across disciplines; multi-dimensional uncertainty assessment and management; scales and scaling issues; combining qualitative and quantitative methods and data; furthering the adoption and impacts of SES modeling on policy; capturing structural changes; representing human dimensions in SES; and leveraging new data types and sources. These challenges limit our ability to effectively use SES modeling to provide the knowledge and information essential for supporting decision making. Whereas some of these challenges are not unique to SES modeling and may be pervasive in other scientific fields, they still act as barriers as well as research opportunities for the SES modeling community. For each challenge, we outline basic steps that can be taken to surmount the underpinning barriers. Thus, the paper identifies priority research areas in SES modeling, chiefly related to progressing modeling products, processes and practices.

More than 50 years ago biologist Garrett Hardin published his influential essay ‘The Tragedy of the Commons’. In his essay, Hardin argued that in situations where people share resources, external intervention via governmental regulations or privatization of the resource is needed to avoid resource overexploitation. While the article is considered by many resource governance scholars as misleading and incomplete, it is one of the most assigned articles in environmental studies courses. Here, we present findings from a survey of instructors who teach undergraduate courses on sustainability within the USA on how Hardin’s essay is used and what the understanding is of the instructors about the essay. The results from the survey demonstrate that there is a mixed understanding of the current state of knowledge about commons governance. In particular, instructors trained in the natural sciences have more misconceptions about commons governance than instructors trained in other disciplines.

Human behaviour is of profound significance in shaping pathways towards sustainability. Yet, the approach to understanding human behaviour in many fields remains reliant on overly simplistic models. For a better understanding of the interface between human behaviour and sustainability, we take work in behavioural economics and cognitive psychology as a starting point, but argue for an expansion of this work by adopting a more dynamic and systemic understanding of human behaviour, that is, as part of complex adaptive systems. A complex adaptive systems approach allows us to capture behaviour as ‘enculturated’ and ‘enearthed’, co-evolving with socio–cultural and biophysical contexts. Connecting human behaviour and context through a complex adaptive systems lens is critical to inform environmental governance and management for sustainability, and ultimately to better understand the dynamics of the Anthropocene itself.

Urban adaptation to climate change is likely to emerge from the responses of residents, authorities, and infrastructure providers to the impact of flooding, water scarcity, and other climate-related hazards. These responses are, in part, modulated by political relationships under cultural norms that dominate the institutional and collective decisions of public and private actors. The legacy of these decisions, which are often associated with investment in hard and soft infrastructure, has lasting consequences that influence current and future vulnerabilities. Making those decisions visible, and tractable is, therefore, an urgent research and political challenge in vulnerability assessments. In this work, we present a modeling framework to explore scenarios of institutional decision-making and socio-political processes and the resultant effects on spatial patterns of vulnerability. The approach entails using multi-criteria decision analysis, agent-based models, and geographic information simulation. The approach allows for the exploration of uncertainties, spatial patterns, thresholds, and the sensitivities of vulnerability outcomes to different policy scenarios. Here, we present the operationalization of the framework through an intentionally simplified model example of the governance of water in Mexico City. We discuss results from this example as part of a larger effort to empirically implement the framework to explore sociohydrological risk patterns and trade-offs of vulnerability in real urban landscapes.

Maintaining safe operating spaces for exploited natural systems in the face of uncertainty is a key sustainability challenge. This challenge can be viewed as a problem in which human society must navigate in a limited space of acceptable futures in which humans enjoy sufficient well-being and avoid crossing planetary boundaries. A critical obstacle is the nature of society as a controller with endogenous dynamics affected by knowledge, values, and decision-making fallacies. We outline an approach for analyzing the role of knowledge infrastructure in maintaining safe operating spaces. Using a classic natural resource problem as an illustration, we find that a small safe operating space exists that is insensitive to the type of policy implementation, while in general, a larger safe operating space exists which is dependent on the implementation of the “right” policy. Our analysis suggests the importance of considering societal response dynamics to varying policy instruments in defining the shape of safe operating spaces.

Even a simple human foraging system has a large number of moving parts. Foragers require a complex decision making process to effectively exploit the spatially and temporally variable resources in an environment. Here we present an agent-based modelling framework, based in optimal foraging theory, for agent foragers to make mobility and foraging decisions by weighing expected caloric returns against geographic and social factors, and forecasted future return rates. We apply our Paleoscape model to a spatially explicit South African coastal landscape to better understand the human foraging system of the Middle Stone Age, when foragers began systematically exploiting a wide variety of flora and fauna in both terrestrial and inter-tidal environments. We also discuss the broader importance of agent-based models of foraging systems for a wide variety of archaeological research questions.

Decision makers often have to act before critical times to avoid the collapse of ecosystems using knowledge that can be incomplete or biased. Adaptive management may help managers tackle such issues. However, because the knowledge infrastructure required for adaptive management may be mobilized in several ways, we study the quality and the quantity of knowledge provided by this knowledge infrastructure. In order to analyze the influence of mobilized knowledge, we study how the following typology of knowledge and its use may impact the safe operating space of exploited ecosystems: (1)knowledge of the past based on a time series distorted by measurement errors; (2)knowledge of the current systems’ dynamics based on the representativeness of the decision makers’ mental models of the exploited ecosystem; (3)knowledge of future eventsbased on decision makers’ likelihood estimates of extreme events based on modeling infrastructure (models and experts to interpret them) they have at their disposal. We consider different adaptive management strategies of a general regulated exploited ecosystem model and we characterize the robustness of these strategies to biased knowledge. Our results show that even with significant mobilized knowledge and optimal strategies, imperfect knowledge may still shrink the safe operating space of the system leading to the collapse of the system. However, we also show that in some cases imperfect knowledge may unexpectedly increase the safe operating space by suggesting cautious strategies. We leverage the quantitative results to frame a discussion focusing on the importance of understanding subtleties of how adaptive knowledge mobilization and knowledge infrastructure affect the robustness of exploited ecosystems.

We report on an art and sustainability project, inspired by sustainable living and by the work of Elinor Ostrom, in which the authors experienced a not-too-distant future of water scarcity in an isolated location in the Mojave Desert for four weeks. We restricted our water use to ≤ 15.1 L/day (4 gallons) water per person and consumed a water-wise vegan diet. Here, we report and reflect on our experience of this art and sustainability project. We show that, as participants, we had no difficulty adjusting to a resource-scarce environment or living in a remote location. Our experience showed that (temporary) behavioral change is possible to cope with extreme resource scarcity without a net negative effect on the quality of life. Future replications of such art and sustainability projects in safer environments could become spaces for science, art, and innovation for more sustainable lifestyles.

Residents of Mexico City experience major hydrological risks, including flooding events and insufficient potable water access for many households. A participatory modeling project, MEGADAPT, examines hydrological risk as co-constructed by both biophysical and social factors and aims to explore alternative scenarios of governance. Within the model, neighborhoods are represented as agents that take actions to reduce their sensitivity to exposure and risk. These risk management actions (to protect their households against flooding and scarcity) are based upon insights derived from focus group discussions within various neighborhoods. We developed a role-playing game based on the model’s rules in order to validate the assumptions we made about residents’ decision-making given that we had translated qualitative information from focus group sessions into a quantitative model algorithm. This enables us to qualitatively validate the perspective and experience of residents in an agent-based model mid-way through the modeling process. Within the context of described hydrological events and the causes of these events, residents took on the role of themselves in the game and were asked to make decisions about how to protect their households against scarcity and flooding. After the game, we facilitated a discussion with residents about whether or not the game was realistic and how it could be improved. The game helped to validate our assumptions, validate the model with community members, and reinforced our connection with the community. We then discuss the potential further development of the game as a learning and communication tool.

The unprecedented use of Earth’s resources by humans, in combination with increasing natural variability in natural processes over the past century, is affecting the evolution of the Earth system. To better understand natural processes and their potential future trajectories requires improved integration with and quantification of human processes. Similarly, to mitigate risk and facilitate socio-economic development requires a better understanding of how the natural system (e.g. climate variability and change, extreme weather events, and processes affecting soil fertility) affects human processes. Our understanding of these interactions and feedback between human and natural systems has been formalized through a variety of modelling approaches. However, a common conceptual framework or set of guidelines to model human–natural-system feedbacks is lacking. The presented research lays out a conceptual framework that includes representing model coupling configuration in combination with the frequency of interaction and coordination of communication between coupled models. Four different approaches used to couple representations of the human and natural system are presented in relation to this framework, which vary in the processes represented and in the scale of their application. From the development and experience associated with the four models of coupled human–natural systems, the following eight lessons were identified that if taken into account by future coupled human–natural-systems model developments may increase their success: (1) leverage the power of sensitivity analysis with models, (2) remember modelling is an iterative process, (3) create a common language, (4) make code open-access, (5) ensure consistency, (6) reconcile spatio-temporal mismatch, (7) construct homogeneous units, and (8) incorporating feedback increases non-linearity and variability. Following a discussion of feedbacks, a way forward to expedite model coupling and increase the longevity and interoperability of models is given, which suggests the use of a wrapper container software, a standardized applications programming interface (API), the incorporation of standard names, the mitigation of sunk costs by creating interfaces to multiple coupling frameworks, and the adoption of reproducible workflow environments to wire the pieces together.

The rapid environmental changes currently underway in many dry regions of the world, and the deep uncertainty about their consequences, underscore a critical challenge for sustainability: how to maintain cooperation that ensures the provision of natural resources when the benefits of cooperating are variable, sometimes uncertain, and often limited. In this work, we present the case of a group of rural communities in a semi-desert region of Chile, where cooperation in the form of labor-sharing has helped maintain higher agriculture yields, group cohesion, and identity. Today, these communities face the challenge of adapting to recurrent droughts, extreme rainfall, and desertification. We formulated an agent-based model to investigate the consequences of regional climate changes on the fate of these labor-exchange institutions. The model, implemented in the framework of prospect theory, simulates the economic decisions of households to engage, or not, in labor-sharing agreements under different scenarios of water supply, water variability, and socio-environmental risk. Results show that the number of fulfilled labor-sharing agreements is reduced by water scarcity and environmental variability. More importantly, defections that involve non-fulfillment of these agreements are more likely to emerge at the intermediate level of environmental variability and water supply stress. These results underscore the need for environmental policy instruments that consider the effects of regional climate changes on the social dynamics of these communities.

Groundwater is one of the most challenging common pool resources to govern, resulting in resource depletion in many areas. We present an innovative use of collective action games to not only measure propensity for cooperation, but to improve local understanding of groundwater interrelationships and stimulate collective governance of groundwater, based on a pilot study in Andhra Pradesh, India. The games simulate crop choice and consequences for the aquifer. These were followed by a community debriefing, which provided an entry point for discussing the interconnectedness of groundwater use, to affect mental models about groundwater. A slightly modified game was played in the same communities, one year later. Our study finds communication within the game increased the likelihood of groups reaching sustainable extraction levels in the second year of play, but not the first. Individual payments to participants based on how they played in the game had no effect on crop choice. Either repeated experience with the games or the revised structure of the game evoked more cooperation in the second year, outweighing other factors influencing behavior, such as education, gender, and trust index scores. After the games were played, a significantly higher proportion of communities adopted water registers and rules to govern groundwater, compared to other communities in the same NGO water commons program. Because groundwater levels are affected by many factors, games alone will not end groundwater depletion. However, games can contribute to social learning about the role of crop choice and collective action, to motivate behavior change toward more sustainable groundwater extraction.

Global groundwater resources are threatened by over-extraction. Castilla-Rho et al. develop an agent-based model of irrigated agriculture based on cooperative and collective action theory, incorporating results from the World Values Survey. The model captures the cultural, socioeconomic, institutional and physical conditions that determine how likely people in different at-risk regions are to comply with regulations.

Behavioral experiments have demonstrated that people do cooperate in commons dilemmas. There are alternative theories that are proposed to explain the data. We will use agent-based models to compare alternative behavioral theories on a series of experimental data of irrigation games. The irrigation dilemma captures situations of asymmetric access to common resources while contributions of all participants are needed to maintain the physical infrastructure.

In our model analysis we compare various alternative theories, including naïve simple ones like selfish rational actors and altruistic actors. We contrast these with various alternative behavioral models for collective action as well as inclusion of other-regarding preferences. The systematic comparison of alternative models on experimental data from 44 groups enables us to test which behavioral theories best explain the observed effects of communication. We do not find that one theory clearly outperform others in explaining the data.

The use of destructive fishing methods is a serious problem, especially for tropical and developing countries. Due to inter temporal nature of fisheries extraction activities, standard economic theory suggests that an individual’s time preference can play a major role in determining the gear choice decision. Based on earlier theoretical work we identify two ways in which individual time preferences can impact the adoption of destructive extraction methods; (i) the conservation effect which posits that patient individuals (as indicated by relatively high discount factor) are less likely to use destructive extraction methods since they are more likely to account for the loss of future income that is accompanied by using these methods, (ii) the disinvestment effect which argues that patient individuals are more likely to use destructive extraction methods since they have greater investment capability.

Using an agent-based model we clarify the conditions under which one of these effects is more dominant than the other one. Our model suggests that the nature of destructive gear along with the level of social dilemma determines whether patient or impatient individuals (relatively lower discount factor) are more likely to adopt such a gear. Additionally agent’s beliefs regarding future resource condition and other agent’s extraction level can have a major influence in some cases.

The planetary boundary framework constitutes an opportunity for decision makers to define climate policy through the lens of adaptive governance. Here, we use the DICE model to analyze the set of adaptive climate policies that comply with the two planetary boundaries related to climate change: (1) staying below a CO₂ concentration of 550 ppm until 2100 and (2) returning to 350 ppm in 2100. Our results enable decision makers to assess the following milestones: (1) a minimum of 33% reduction of CO₂ emissions by 2055 in order to stay below 550 ppm by 2100 (this milestone goes up to 46% in the case of delayed policies); and (2) carbon neutrality and the effective implementation of innovative geoengineering technologies (10% negative emissions) before 2060 in order to return to 350 ppm in 2100, under the assumption of getting out of the baseline scenario without delay. Finally, we emphasize the need to use adaptive path-based approach instead of single point target for climate policy design.

Small holder agricultural systems, strongly dependent on water resources and investments in shared infrastructure, make a significant contribution to food security in developing countries. These communities are increasingly integrated in the global economy and are exposed to new global climate-related risks that may affect their willingness to cooperate in community level collective action problems. We performed field experiments on public goods with private and collective risks in 118 small-scale rice producing communities in four countries. Our results indicate that increasing integration of those communities with the broader economic system is associated with lower investments in public goods when facing collective risks. These findings indicate that local public good provision may be negatively affected by collective risks especially if communities are more integrated with the market economy.

Social identities are among the key factors driving behavior in complex societies. Signals of social identity are known to influence individual behaviors in the adoption of innovations. Yet the population-level consequences of identity signaling on the diffusion of innovations are largely unknown. Here we use both analytical and agent-based modeling to consider the spread of a beneficial innovation in a structured population in which there exist two groups who are averse to being mistaken for each other. We investigate the dynamics of adoption and consider the role of structural factors such as demographic skew and communication scale on population-level outcomes. We find that outgroup aversion can lead to adoption being delayed or suppressed in one group, and that population-wide underadoption is common. Comparing the two models, we find that differential adoption can arise due to structural constraints on information flow even in the absence of intrinsic between-group differences in adoption rates. Further, we find that patterns of polarization in adoption at both local and global scales depend on the details of demographic organization and the scale of communication. This research has particular relevance to widely beneficial but identity-relevant products and behaviors, such as green technologies, where overall levels of adoption determine the positive benefits that accrue to society at large.

To evaluate the concern over the reproducibility of computational science, we reviewed 2367 journal articles on agent-based models published between 1990 and 2014 and documented the public availability of source code. The percentage of publications that make the model code available is about 10%. The percentages are similar for publications that are reportedly dependent on public funding. There are big differences among journals in the public availability of model code and software used. This suggests that the varying social norms and practical convenience around sharing code may explain some of the differences among different sectors of the scientific community.

Formal models are commonly used in natural resource management (NRM) to study human-environment interactions and inform policy making. In the majority of applications, human behaviour is represented by the rational actor model despite growing empirical evidence of its shortcomings in NRM contexts. While the importance of accounting for the complexity of human behaviour is increasingly recognized, its integration into formal models remains a major challenge. The challenges are multiple: i) there exist many theories scattered across the social sciences, ii) most theories cover only a certain aspect of decision-making, iii) they vary in their degree of formalization, iv) causal mechanisms are often not specified. We provide a framework- MoHuB (Modelling Human Behavior) – to facilitate a broader inclusion of theories on human decision-making in formal NRM models. It serves as a tool and common language to describe, compare and communicate alternative theories. In doing so, we not only enhance understanding of commonalities and differences between theories, but take a first step towards tackling the challenges mentioned above. This approach may enable modellers to find and formalize relevant theories, and be more explicit and inclusive about theories of human decision making in the analysis of social-ecological systems.

Large scale collaboration is a fundamental characteristic of human society, and has recently manifested in the development and proliferation of online communities. These virtual social spaces provide an opportunity to explore large scale collaborations as natural experiments in which determinants of success can be tested. In order to do this, we first review previous work on meddling online communities to build an understanding of how these communities function. Having thus identified the operating mechanisms inherent in online communities, we propose a population ecology model of online communities that seeks to explain a number of statistical patterns from a selection of such communities.

Our understanding of human behavior is limited and consequently lacks a standard formal model of human behavior that could represent relevant behavior in social-ecological systems. In this paper we explore the consequences of alternative behavioral models using a simple dynamic system of agents of harvesting daisies in the well-known Daisyworld model. We explore the consequences of different behavioral assumptions and derive optimal tax policies that lead to sustainable outcomes for each of the theories.

We find that the flow of attention on the Web forms a directed, tree-like structure implying the time-sensitive browsing behavior of users. Using the data of a news sharing website, we construct clickstream networks in which nodes are news stories and edges represent the consecutive clicks between two stories. To identify the flow direction of clickstreams, we define the “flow distance” of nodes (L_i), which measures the average number of steps a random walker takes to reach the ith node. It is observed that L_i is related with the clicks (C_i) to news stories and the age (T_i) of stories. Putting these three variables together help us understand the rise and decay of news stories from a network perspective. We also find that the studied clickstream networks preserve a stable structure over time, leading to the scaling between users and clicks. The universal scaling behavior is confirmed by the 1,000 Web forums. We suggest that the tree-like, stable structure of clickstream networks reveals the time-sensitive preference of users in online browsing. To test our assumption, we discuss three models on individual browsing behavior and compare the simulation results with empirical data.

Institutions, the rules of the game that shape repeated human interactions, clearly play a critical role in helping groups avoid the inefficient use of shared resources such as fisheries, freshwater, and the assimilative capacity of the environment. Institutions, however, are intimately intertwined with the human, social, and biophysical context within which they operate. Scholars typically are careful to take this context into account when studying institutions and Ostrom’s Institutional Design Principles are a case in point. Scholars have tested whether Ostrom’s Design Principles, which specify broad relationships between institutional arrangements and context, actually support successful governance of shared resources. This article further contributes to this line of research by leveraging the notion of institutional design to outline a research trajectory focused on coupled infrastructure systems in which institutions are seen as one class of infrastructure among many that dynamically interact to produce outcomes over time.

Large-N comparative studies have helped common pool resource scholars gain general insights into the factors that influence collective action and governance outcomes. However, these studies are often limited by missing data, and suffer from the methodological limitation that important information is lost when we reduce textual information to quantitative data. This study was motivated by nine case studies that appeared to be inconsistent with the expectation that the presence of Ostrom’s Design Principles increases the likelihood of successful common pool resource governance. These cases highlight the limitations of coding and analysing Large-N case studies. We examine two issues: 1) the challenge of missing data and 2) potential approaches that rely on context (which is often lost in the coding process) to address inconsistencies between empirical observations theoretical predictions.  For the latter, we conduct a post-hoc qualitative analysis of a large-N comparative study to explore 2 types of inconsistencies: 1) cases where evidence for nearly all design principles was found, but available evidence led to the assessment that the CPR system was unsuccessful and 2) cases where the CPR system was deemed successful despite finding limited or no evidence for design principles.  We describe inherent challenges to large-N comparative analysis to coding complex and dynamically changing common pool resource systems for the presence or absence of design principles and the determination of “success”.  Finally, we illustrate how, in some cases, our qualitative analysis revealed that the identity of absent design principles explained inconsistencies hence de-facto reconciling such apparent inconsistencies with theoretical predictions.  This analysis demonstrates the value of combining quantitative and qualitative analysis, and using mixed-methods approaches iteratively to build comprehensive methodological and theoretical approaches to understanding common pool resource governance in a dynamically changing context.

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.

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 Destign 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 bounduaries 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.

Groundwater is a common-pool resource that is subject to depletion in many places around the world as a result of increased use of irrigation and water-demanding cash crops. Where state capacity to control groundwater use is limited, collective action is important to increase recharge and restrict highly water-consumptive crops. We present results of field experiments in hard rock areas of Andhra Pradesh, India, to examine factors affecting groundwater use. Two nongovernmental organizations (NGOs) ran the games in communities where they were working to improve watershed and water management. Results indicate that, when the links between crop choice and groundwater depletion is made explicit, farmers can act cooperatively to address this problem. Longer NGO involvement in the villages was associated with more cooperative outcomes in the games. Individuals with more education and higher perceived community social capital played more cooperatively, but neither gender nor method of payment had a significantly effect on individual behavior. When participants could repeat the game with communication, similar crop choice patterns were observed. The games provided an entry point for discussion on the understanding of communities of the interconnectedness of groundwater use and crop choice.

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.

Improving the adaptive capacity of small-scale irrigation systems to the impacts of climate change is crucial for food security in Asia. This study analyzes the capacity of small-scale irrigation systems dependent on the Asian monsoon to adapt to variability in river discharge caused by climate change. Our study is motivated by the Pumpa irrigation system, a small-scale irrigation system located in Nepal that is a model for this type of system. We developed an agent-based model in which we simulated the decisions farmers make about the irrigation strategy to use according to available water flow. Given the uncertainty associated with how climate change may affect the Asian monsoon, we simulated the performance of the system under different projections of climate change in the region (increase and decrease in rainfall, reduction and expansion of the monsoon season, and changes in the timing of the onset of the monsoon). Accordingly to our simulations, farmers might need to adapt to rainfall intensification and a late onset in the monsoon season. The demands for collective action among farmers (e.g. infrastructure repair, meetings, decisions, etc.) might increase considerably due to climate change. Although our model suggests that investment in new infrastructure might increase the performance of the system under some climate change scenarios, the high inequality among farmers when water availability is reduced might hinder the efficiency of these measures due to a reduction of farmers’ willingness to cooperate. Our modeling exercise helps to hypothesize about the most sensitive climate change scenarios for smallscale irrigation farming in Nepal and helps to frame a discussion of some possible solutions and fundamental trade-offs in the process of adaptation to improve for food and water security under climate change.

Keywords: Adaptation; Agent-based model; Climate change; Common-pool resources; Irrigation systems; Resilience

In traditional public good experiments participants receive an endowment from the experimenter that can be invested in a public good or kept in a private account. In this paper we present an experimental environment where participants can invest time during five days to contribute to a public good. Participants can make contributions to a linear public good by logging into a web application and performing virtual actions. We compared four treatments, with different group sizes and information of (relative) performance of other groups. We find that information feedback about performance of other groups has a small positive effect if we control for various attributes of the groups. Moreover, we find a significant effect of the contributions of others in the group in the previous day on the number of points earned in the current day. Our results confirm that people participate more when participants in their group participate more, and are influenced by information about the relative performance of other groups.

Information sharing is a critical task for group-living animals. The pattern of sharing can be modeled as a network whose structure can affect the decision-making performance of individual members as well as that of the group as a whole. A fully connected network, in which each member can directly transfer information to all other members, ensures rapid sharing of important information, such as a promising foraging location. However, it can also impose costs by amplifying the spread of inaccurate information (if, for example the foraging location is actually not profitable). Thus, an optimal network structure should balance effective sharing of current knowledge with opportunities to discover new information. We used a computer simulation to measure how well groups characterized by different network structures (fully connected, small world, lattice, and random) find and exploit resource peaks in a variable environment. We found that a fully connected network outperformed other structures when resource quality was predictable. When resource quality showed random variation, however, the small world network was better than the fully connected one at avoiding extremely poor outcomes. These results suggest that animal groups may benefit by adjusting their information-sharing network structures depending on the noisiness of their environment.

Keywords: agent-based model; collective cognition; conformity; small world networks; speed–accuracy; trade-off

Online communities are becoming increasingly important as platforms for large-scale human cooperation. These communities allow users seeking and sharing professional skills to solve problems collaboratively. To investigate how users cooperate to complete a large number of knowledge-producing tasks, we analyze Stack Exchange, one of the largest question and answer systems in the world. We construct attention networks to model the growth of 110 communities in the Stack Exchange system and quantify individual answering strategies using the linking dynamics on attention networks. We identify two answering strategies. Strategy A aims at performing maintenance by doing simple tasks, whereas strategy B aims at investing time in doing challenging tasks. Both strategies are important: empirical evidence shows that strategy A decreases the median waiting time for answers and strategy B increases the acceptance rate of answers. In investigating the strategic persistence of users, we find that users tends to stick on the same strategy over time in a community, but switch from one strategy to the other across communities. This finding reveals the different sets of knowledge and skills between users. A balance between the population of users taking A and B strategies that approximates 2:1, is found to be optimal to the sustainable growth of communities.

Encouragement of learning is considered to be central to resilience of social–ecological systems (SESs) to unknown and unforeseeable shocks. However, despite the consensus on the centrality of learning, little research has been done on the details of how learning should be encouraged to enhance adaptive capacity for resilience. This study contributes to bridging this research gap by examining the existing data from a behavioral experiment on SES that involves learning. We generate new hypotheses regarding how learning should be encouraged by comparing the learning processes of human-subject groups that participated in the experiment. Our findings suggest that under environmental stability, groups may be able to perform well without frequent outer-loop (or double-loop) learning. They can still succeed as long as they tightly coordinate on shared strategies along with active monitoring of SESs and user participation in decision-making. However, such groups may be fragile under environmental variability. Only the groups that experience active outer-loop learning and monitoring of SESs are likely to remain resilient under environmental variability.

Keywords: Loop learning; General resilience; Behavioral experiment; Adaptive management; Adaptive co-management; Adaptive governance

We used psychological methods to investigate how two prominent interventions, participatory decision making and en- forcement, influence voluntary cooperation in a common-pool resource dilemma. Groups (N=40) harvested resources from a shared resource pool. Individuals in the Voted-Enforce condition voted on conservation rules and could use economic sanc- tions to enforce them. In other conditions, individuals could not vote (Imposed-Enforce condition), lacked enforcement (Voted condition), or both (Imposed condition). Cooperation was strongest in the Voted-Enforce condition (Phase 2). Moreover, these groups continued to cooperate voluntarily after enforcement was removed later in the experiment. Cooperation was weakest in the Imposed-Enforce condition and degraded after enforcement ceased. Thus, enforcement improved voluntary cooperation only when individuals voted. Perceptions of procedural justice, self-determination, and security were highest in the Voted- Enforced condition. These factors (legitimacy, security) increased voluntary cooperation by promoting rule acceptance and internalized motivation. Voted-Enforce participants also felt closer to one another (i.e., self-other merging), further contribut- ing to their cooperation. Neither voting nor enforcement produced these sustained psychological conditions alone. Voting lacked security without enforcement (Voted condition), so the individuals who disliked the rule (i.e., the losing voters) pil- laged the resource. Enforcement lacked legitimacy without voting (Imposed-Enforce condition), so it crowded out internal reasons for cooperation. Governance interventions should carefully promote security without stifling fundamental needs (e.g., procedural justice) or undermining internal motives for cooperation.

Keywords: cooperation, internalized motivation, institutional acceptance, resource dilemma, social dilemma, voting, sanc- tions, motivational crowding, procedural justice, self-determination, self-other merging.

When governing shared resources, the level and quality of information available to resource users on the actions of others and the state of the environment may have a critical effect on the performance of groups. In the work presented here, we find that lower availability of information does not affect the average performance of the group in terms of their capacity to provide public infrastructure and govern resource use, but it affects the distribution of earnings and the ability to cope with disturbances. We performed behavioral experiments that mimic irrigation dilemmas in which participants need to maintain infrastructure function in order to generate revenue from the use of water. In the experimental design, there is an upstream–downstream asymmetry of access to water that may lead to unequal access to water. We find that inequality of investment in irrigation infrastructure and water appropriation across players is more pronounced in experiments where resource users have limited information about the actions of others. We also find that inequality is linked to the ability of groups to cope with disturbances. Hence a reduced level of information indirectly reduces the adaptive capacity of groups.

Keywords: Public infrastructure; Experimental economics; Inequality; Communication; Asymmetric commons dilemma

The rational thinking assumption by mainstream economics has a far distance from real people. This paper designs a series of behavioral economic experiments (trust, prisoners’ dilemma, public good, dictator, and ultimatum games) and conducts them in two university classrooms in China and the USA. It shows that people intrinsically have goodness and social thinking, and can provide public goods voluntarily, and have a fair preference for economic interest distribution. However, the American students show a higher trust degree and cooperation level, and stronger preferences of cooperation and fairness than the Chinese ones. Therefore, this paper suggests that policymakers are necessary to fully understand people’s social thinking and micro behavior and they are necessary to emphasize publicizing this kind of thinking, ability, and action and should provide an information platform for people to solve collective dilemmas voluntarily.

Keywords:  Goodness; Thinking Socially; Voluntary Provision; Fair Distribution; Behavioral Economic Experiments

摘 要:主流经济学的理性思维与现实中人的思维存在偏差。本文设计了一系列行为经济实验 (信任、囚徒困境、公共品、独裁和最后通牒实验) 并在中美两国大学课堂上实施。研究表明:人们 天生具有善意本质和社会性思维,能够自愿供给公共品,偏好经济利益的公平分配;而在信任度、合 作偏好、合作水平和公平偏好的量化方面,美方都表现出更高 (强)的特征。本文建议政策制定者 有必要充分了解人们的社会性思维及相应的微观行为,政策的重点有必要充分考虑到这些思维、能 力和行动,以及为人们自愿解决集体行动问题提供信息平台。

Research on collective action and common-pool resources is extensive. However, little work has concentrated on the effect of variability in resource availability and collective action, especially in the context of asymmetric access to resources. Earlier works have demonstrated that environmental variability often leads to a reduction of collective action in the governance of shared resources. Here we assess how environmental variability may impact collective action. We performed a behavioral experiment involving an irrigation dilemma. In this dilemma participants invested first into a public fund that generated water resources for the group, which were subsequently appropriated by one participant at a time from head end to tail end. The amount of resource generated for the given investment level was determined by a payoff table and a stochastic event representing environmental variability, i.e., rainfall. Results show that that (1) upstream users’ behavior is by far the most important variable in determining the outcome of collective action; (2) environmental variability (i.e. risk level in investing in the resource) has little effect on individual investment and extraction levels; and (3) the action-reaction feedback is fundamental in determining the success or failure of communities.

Keywords: asymmetry; common-pool resources; feedbacks; laboratory experiments; trust; variability

To better understand the origins of modern humans, we are developing a paleoscape model that simulates the climatic conditions and distribution of natural resources available to humans during this critical stage of human evolution. Our geographic focus is the southern Cape region of South Africa, which was rich in natural resources for hunter-gatherer groups including edible plants, shellfish, animals, and raw materials. We report our progress in using the Extreme Science and Engineering Discovery Environment (XSEDE) to realize the paleoscape model, which consists of four components: a climate model, correlative and dynamic vegetation models, and agent-based models. We adopt a workflow-based approach that combines modeling and data analytics to couple these four modeling components using XSEDE. We have made significant progress in scaling climate and agent-based models on XSEDE. Our next steps will be to couple these models to the vegetation models to complete the workflow, which will require overcoming multiple theoretical, methodological, and technical challenges.

Social roles are thought to play an important role in determining the capacity for collective action in a community regarding the use of shared resources. Here we report on the results of a study using a behavioral experimental approach regarding the relationship between social roles and the performance of social-ecological systems. The computer-based irrigation experiment that was the basis of this study mimics the decisions faced by farmers in small-scale irrigation systems. In each of 20 rounds, which are analogous to growing seasons, participants face a two-stage commons dilemma. First they must decide how much to invest in the public infrastructure, e.g., canals and water diversion structures. Second, they must decide how much to extract from the water made available by that public infrastructure. Each round begins with a 60-second communication period before the players make their investment and extraction decisions. By analyzing the chat messages exchanged among participants during the communication stage of the experiment, we coded up to three roles per participant using the scheme of seven roles known to be important in the literature: leader, knowledge generator, connector, follower, moralist, enforcer, and observer. Our study supports the importance of certain social roles (e.g., connector) previously highlighted by several case study analyses. However, using qualitative comparative analysis we found that none of the individual roles was sufficient for groups to succeed, i.e., to reach a certain level of group production. Instead, we found that a combination of at least five roles was necessary for success. In addition, in the context of upstream-downstream asymmetry, we observed a pattern in which social roles assumed by participants tended to differ by their positions. Although our work generated some interesting insights, further research is needed to determine how robust our findings are to different action situations, such as biophysical context, social network, and resource uncertainty.

Keywords: behavioral experiments; communication; irrigation systems; lab experiments; qualitative comparative analysis; social-ecological networks; social-ecological systems; social roles

Sustainability theory can help achieve desirable social-ecological states by generalizing lessons across contexts and improving the design of sustainability interventions. To accomplish these goals, we argue that theory in sustainability science must (1) explain the emergence and persistence of social-ecological states, (2) account for endogenous cultural change, (3) incorporate cooperation dynamics, and (4) address the complexities of multilevel social-ecological interactions. We suggest that cultural evolutionary theory broadly, and cultural multilevel selection in particular, can improve on these fronts. We outline a multilevel evolutionary framework for describing social-ecological change and detail how multilevel cooperative dynamics can determine outcomes in environmental dilemmas. We show how this framework complements existing sustainability frameworks with a description of the emergence and persistence of sustainable institutions and behavior, a means to generalize causal patterns across social-ecological contexts, and a heuristic for designing and evaluating effective sustainability interventions. We support these assertions with case examples from developed and developing countries in which we track cooperative change at multiple levels of social organization as they impact social-ecological outcomes. Finally, we make suggestions for further theoretical development, empirical testing, and application.

Keywords: cooperation; cultural evolution; multilevel selection; sustainability; theory

Paleoanthropologists (scientists studying human origins) universally recognize the evolutionary significance of ancient climates and environments for understanding human origins.[1-6] Even those scientists working in recent phases of human evolution, when modern humans evolved, agree that hunter-gatherer adaptations are tied to the way that climate and environment shape the food and technological resource base.[7-10] The result is a long tradition of paleoanthropologists engaging with climate and environmental scientists in an effort to understand if and how hominin bio-behavioral evolution responded to climate and environmental change. Despite this unusual consonance, the anticipated rewards of this synergy are unrealized and, in our opinion, will not reach potential until there are some fundamental changes in the way the research model is constructed. Discovering the relation between climate and environmental change to human origins must be grounded in a theoretical framework and a causal understanding of the connection between climate, environment, resource patterning, behavior, and morphology, then move beyond the strict correlative research that continues to dominate the field.

We use an agent-based model to analyze the effects of spatial heterogeneity and agents’ mobility on social–ecological outcomes. Our model is a stylized representation of a dynamic population of agents moving and harvesting a renewable resource. Cooperators (agents who harvest an amount close to the maximum sustainable yield) and selfish agents (those who harvest an amount greater than the sustainable yield) are simulated in the model. Three indicators of the outcomes of the system are analyzed: the number of settlements, the resource level, and the proportion of cooperators in the population. Our paper adds a more realistic approach to previous studies on the evolution of cooperation by considering a social–ecological system in which agents move in a landscape to harvest a renewable resource. Our results conclude that resource dynamics play an important role when studying levels of cooperation and resource use. Our simulations show that the agents’ mobility significantly affects the outcomes of the system. This response is nonlinear and very sensible to the type of spatial distribution of the resource richness. In our simulations, better outcomes of long-term sustainability of the resource are obtained with moderate agent mobility and cooperation is enhanced in harsh environments with low resource level in which cooperative groups have natural boundaries fostered by agents’ low mobility.

Keywords: Agent-based model; Cooperation; Heterogeneous landscape; Mobility; Social–ecological systems; Spatial heterogeneity

During the last 40 years evidence from systematic case study analysis and behavioral experiments have provided a comprehensive perspective on how communities can manage common resources in a sustainable way. The conventional theory based on selfish rational actors cannot explain empirical observations. A more comprehensive theoretical framework of human behavior is emerging that include concepts such as trust, conditional cooperation, other-regarding preferences, social norms, and reputation. The new behavioral perspective also demonstrates that behavioral responses depend on social and biophysical context.

We develop an agent-based model of foraging behavior based on ecological parameters of the environment and prey characteristics measured in the Mbaracayu Reserve Paraguay. We then compare estimated foraging behavior from our model to the ethnographically observed behavior of Ache hunter–gatherers who inhabit the region and show a close match for daily harvest rates, time allocation, and species composition of prey. The model allows us to explore the implications of social living, cooperative hunting, variation in group size and mobility, under Ache-like ecological conditions. Simulations show that social living decreases daily risk of no food, but cooperative hunting has only a modest effect on mean harvest rates. Analysis demonstrates that bands should contain 7–8 hunters who move nearly every day in order to achieve the best combination of average harvest rates and low probability of no meat in camp.

Keywords: Optimal foraging theory; Agent-based modeling

Recently, there has been an increased interest in using behavioral experiments to study hypotheses on the governance of social-ecological systems. A diversity of software tools are used to implement such experiments. We evaluated various publicly available platforms that could be used in research and education on the governance of social-ecological systems. The aims of the various platforms are distinct, and this is noticeable in the differences in their user-friendliness and their adaptability to novel research questions. The more easily accessible platforms are useful for prototyping experiments and for educational purposes to illustrate theoretical concepts. To advance novel research aims, more elaborate programming experience is required to either implement an experiment from scratch or adjust existing experimental software. There is no ideal platform best suited for all possible use cases, but we have provided a menu of options and their associated trade-offs.

Keywords: education; lab experiments; research; software

Allowing resource users to communicate in behavioural experiments on commons dilemmas increases the level of cooperation. In actual common pool resource dilemmas in the real world, communication is costly, which is an important detail missing from most typical experiments. We conducted experiments where participants must give up harvesting opportunities to communicate. The constrained communication treatment is compared with the effect of limited information about the state of the resource and the actions of the other participants. We find that despite making communication costly, performance of groups improves in all treatments with communication. We also find that constraining communication has a more significant effect than limiting information on the performance of groups.

Keywords: common pool resource, conditional cooperation, costly communication, lab experiments, limited information

 
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.

Keywords: Public good games; group selection; other-regarding preferences; conditional cooperation

We present a repository for disseminating the computational models associated with publications in the social and life sciences. The number of research projects using computational models has been steadily increasing but the resulting publications often lack model code and documentation which hinders replication, verification of results and accumulation of knowledge. We have developed an open repository, the CoMSES Net Computational Model Library, to address this problem. Submissions to the library can be original models accompanying publications or replications of previous studies. Researchers can request that their models undergo a certification process that verifies that the model code successfully compiles and runs and that it follows documentation best practices. Models that pass the certification process are assigned persistent URLs and identifiers. We present the basic components of our repository, discuss our initial experiences with the library, and elaborate on future steps in the development of this cyberinfrastructure.

Keywords: Model archive; Open source; Computational modeling; Documentation; Agent-based modeling

The ability of groups to self-govern their common-pool resources is well documented (Ostrom, 1990). Whether common-pool resources are fish stocks or freshwater or forest products, the success of self-governance relates to the ability of appropriators to develop trust relationships, monitor and enforce agreements, and communicate among each other.

All major Indian cities face a severe transport crisis, with the number of cars on the road increasing every day. Policy makers are trying to keep pace with this growth by supplying more roads, largely neglecting demand-side policy measures. We have developed an economic experiment to investigate behavioral responses of citizens to such measures. Drawing on a sample of 204 white-collar commuters from Hyderabad, India, we model mode choice as a coordination problem and analyze how bus subsidies, increased parking costs, and public information on preferential car use can affect mode choice. We find that pecuniary treatments are effective for shifting behavior towards socially more desirable outcomes and increasing total benefits. Mode choice is relatively unaffected by socio-economic variables like gender, education or income but is significantly affected by actual traffic behavior. We discuss limitations of the applied sampling, conclude with a critical evaluation of the strengths and weaknesses of economic experiments in transportation research, and offer an outlook on how further experimentation could enrich the policy debate.

Keywords: Coordination game; Experimental economics; Hyderabad; India; Mode switching; Public transport

In recent years there has been a shift in biodiversity efforts from protected areas to one of interlinked habitat patches across multiple land tenure types. Much work remains on how managers can intervene in such systems to achieve basic goals. We use an agent-based model of a metapopulation with predator–prey dynamics and density-dependent migration to examine theoretically the capacity of a manager to modify the ecosystem to achieve conservation goals. We explore management strategies aimed at maintaining one of two goals – local or global coexistence of species. To achieve their goal, the manager varies the connectivity between patches based on one of three strategies – the monitoring of predator, prey, or the vegetation carrying capacity of the patches. We find that strategies that lead to highest coexistence monitor mid-tier populations globally. Our goal is to use our model results to advance decision-making in conservation beyond protected areas, typical in today’s conservation.

Keywords: Conservation; Biodiversity; Population dynamics; Management; Adaptive management; Agent-based modeling

This chapter described the empirical calibration of a theoretical model based on data from field experiments. Field experiments on irrigation dilemmas were performed to understand how resource users overcome asymmetric collective action problems. The fundamental problem facing irrigation systems is how to solve two related collective action problems: (1) the provision of the physical and ecological infrastructure necessary to utilize the resource (water), and (2) the irrigation dilemma where the relative positions of “head-enders” and “tail-enders” generate a sequential access to the resource itself (water). If actors act as rational, self-interested, agents, it is difficult to understand how irrigation infrastructure would ever be constructed and maintained by the farmers obtaining water from a system as contrasted to a government irrigation bureaucracy. Wittfogel (1957) argued that a central control was indispensable for the functioning of larger irrigation systems and hypothesized that some state-level societies have emerged as a necessary side-effect of solving problems associated with the use of large-scale irrigation.

In this paper we apply the updated consumat approach to the case of diffusion of electric cars. We will discuss how data from a large sample can be used to parameterize a number of main behavioural drivers, and how these relate to behavioural processes. At this stage we explain how the data fit in the framework, and whereas a model is currently under development, first simulation results are to be available first during the ESSA conference.

Keywords: diffusion; electric cars; agent based modeling; human behavior; decision making; needs; consumat

Elinor Ostrom was a leader in using multiple methods to perform institutional analysis. In this paper, we discuss how a multi-method approach she pioneered may be used to study the robustness of social–ecological systems. We synthesize lessons learned from a series of studies on small-scale irrigation systems in which we use case-study analysis, experimental methods in laboratory and field settings, and mathematical models. The accumulated insights show the importance of creating institutional arrangements that fit the human ecology within the biophysical constraints of the system. The examples of work based on multiple methods approaches presented here highlight several lessons. For example, experimental work helps us better understand the details of how the ability to maintain trust relationships, low levels of inequality, and low transaction costs of coordination are critical for success. Likewise, the integration of case-study analysis and modeling helps us better understand how systems that can leverage biophysical characteristics to help address challenges of monitoring, sanctioning, and coordination may be able to increase their chances of success.

Cyber security defense is often performed by a group of people called cyber defense analysts and yet team work and collaboration in cyber defense is almost non-existent. This study, using an agent-based model of the cyber defense analyst’s task and interactions, explored the effects of different collaboration strategies and team sizes on performance measures such as number of intrusion alerts accurately processed by the analysts and rewards they accrue from accurately processing the alerts. This study also explored the feasibility of using agent-based modeling methodologies for studying team processes in the cyber defense context. The model revealed that specific collaboration strategies lead to better performance and that large teams are detrimental to performance.

The structure and dynamics of ecosystems can affect the information available to resource users on the state of the common resource and the actions of other resource users. We present results from laboratory experiments that showed that the availability of information about the actions of other participants affected the level of cooperation. Since most participants in commons dilemmas can be classified as conditional cooperators, not having full information about the actions of others may affect their decisions. When participants had more information about others, there was a more rapid reduction of the resource in the first round of the experiment. When communication was allowed, limiting the information available made it harder to develop effective institutional arrangements. When communication was not allowed, there was a more rapid decline of performance in groups where information was limited. In sum, the results suggest that making information available to others can have an important impact on the conditional cooperation and the effectiveness of communication.

Keywords: common pool resource; communication; conditional cooperation; information; institutions

A framework is presented to simulate and analyze the effect of multiple business scenarios on the adoption behavior of a group of technology products. Diffusion is viewed as an emergent phenomenon that results from the interaction of consumers. An agent-based model is used in which potential adopters of technology product are allowed to be influenced by their local interactions within the social network. Along with social influence, the effect of product features is important and we ascribe feature sensing attributes to the consumer agents along with sensitivities to social influence. The model encompasses utility theory and discrete choice models in the decision-making process for the consumers. We use expressive machine learning algorithms that can handle complex, nonlinear, and interactive effects to identify important inputs that contribute to the model and to graphically summarize their effects. We present a realistic case study that demonstrates the ability of this framework to model changes in market shares for a group of products in response to business scenarios such as new product introduction and product discontinuation under different pricing strategies. The models and other tools developed here are envisioned to be a part of a recommender system that provides insights into the effects of various business scenarios on shaping market shares of different product groups.

Keywords: Scenario analysis; technology substitution; dependency plots

We conceptualize social-ecological systems (SESs) as complex adaptive systems where public policy affects and is affected by the biophysical system in which it is embedded. The study of robustness of SESs combines insights from various disciplines including economics, political science, ecology, and engineering. In this paper we present an approach that can be used to explore the implications for public policy when viewed as a component of a complex adaptive system. Our approach leverages the Institutional Analysis and Development framework to provide a platform for interdisciplinary research that focuses on system-wide outcomes of the policy process beyond just policy change. The main message is that building robustness can create new vulnerabilities. Fail-free policies cannot be developed, and instead of a focus on the “right” policy, we need to think about policy processes that stimulate experimentation, adaptation, and learning.

Studies of collective action in commons dilemmas in social–ecological systems typically focus on scenarios in which actors all share symmetric (or similar) positions in relation to the common-pool resource. Many common social–ecological systems do not meet these criteria, most notably, irrigation systems. Participants in irrigation systems must solve two related collective action problems: 1) the provisioning of physical infrastructure necessary to utilize the resource (water), and 2) the asymmetric common-pool resource dilemma where the relative positions of “head-enders” and “tail-enders” generate asymmetric access to the resource itself (water). In times of scarcity, head-enders have an incentive to not share water with tail-enders. Likewise, tail-enders have an incentive to not provide labor to maintain the system if they do not receive water. These interdependent incentives may induce a cooperative outcome under favorable conditions. However, how robust is this system of interdependent incentives in the presence of environmental variability that generates uncertainty about water availability either through variation in the water supply itself or through shocks to infrastructure? This paper reports on results from laboratory experiments designed to address this question.

Keywords: Commons dilemmas; Uncertainty; Experiments; Collective action; Irrigation

Harvesting from common resources has been studied through experimental work in the laboratory and in the field. In this paper we report on a dynamic commons experiment, representing a forest, performed with different types of communities of resource users in Thailand and Colombia, as well as student participants. We find that all groups overharvest the resource in the first part of the experiment and that there is no statistical difference between the various types of groups. In the second part of the experiment, participants appropriate the common resource after one of three possible regulations is elected and implemented. There is less overharvesting after the rules are implemented, but there is a significant amount of rule breaking. The surprising finding is that Colombian villagers break the rules of the games more often than other groups, and even more so when they have more trust in members of the community. This observation can be explained by the distrust in externally proposed regulations due to the institutional and cultural context.

Keywords: Common pool resources; Dynamic games; Forestry; Field experiments; Rule compliance

Globalization and global climate change will probably be accompanied by rapid social and biophysical changes that may be caused by external forcing or internal nonlinear dynamics. These changes often subject residing populations (human or otherwise) to harsh environments and force them to respond. Research efforts have mostly focused on the underlying mechanisms that drive these changes and the characteristics of new equilibria towards which populations would adapt. However, the transient dynamics of how populations respond under these new regimes is equally, if not more, important, and systematic analysis of such dynamics has received less attention. Here, we investigate this problem under the framework of replicator dynamics with fixed reward kernels. We show that at least two types of population responses are possible—cohesive and population-dividing transitions—and demonstrate that the critical transition between the two, as well as other important properties, can be expressed in simple relationships between the shape of reward structure, shift magnitude and initial strategy diversity. Importantly, these relationships are derived from a simple, yet powerful and versatile, method. As many important phenomena, from political polarization to the evolution of distinct ecological traits, may be cast in terms of division of populations, we expect our findings and method to be useful and applicable for understanding population responses to change in a wide range of contexts.

Increased landscape fragmentation can have deleterious effects on terrestrial biodiversity. The use of protected areas, as islands of conservation, has limits to the extent of biodiversity conservation due to isolation and scale. As a result, there is a push to transition from solely developing protected areas to policies that also support corridor management. Given the complexities of multi-species interaction on a fragmented landscape, managers need additional tools to aid in decision-making and policy development. We develop an agent-based model (ABM) of a two-patch metapopulation with local predator–prey dynamics and variable, density-dependent species dispersal. The goal is to assess how connectivity between patches, given a variety of dispersal schema for the targeted interacting populations, promotes coexistence among predators and prey. The experiment conducted suggests that connectivity levels at both extremes, representing very little risk and high risk of species mortality, do not augment the likelihood of coexistence while intermediate levels do. Furthermore, the probability of coexistence increases and spans a wide range of connectivity levels when movement is less probabilistic and more dependent on population feedback. Knowledge of these connectivity tradeoffs is essential for assessing the value of habitat corridors, and can be further elucidated under the agent-based framework.

Keywords: Landscape fragmentation; Habitat connectivity; Predator–prey; Agent-based model; Metapopulation; Density-dependent dispersal

This paper reports the results of the inaugural modeling competition sponsored by the Network for Computational SocioEcological Sciences (CoMSES Network). Competition participants were provided with a dataset collected from human-subjects experiments and were asked to develop an agent-based model that replicated behavioral patterns reflected in the data with the goal of using the model to predict behavioral changes in a slightly modified experimental treatment. The data were collected in a resource foraging experiment in which human subjects moved avatars on a computer screen to harvest tokens in a common pool resource. In the original experiments, on which the competition participants based their models, the subjects possessed full information about the state of the resource and the actions of the other group members sharing the resource. The competition challenged participants to predict what would happen if the experimental subjects had limited vision. Using only the data from the original experiment, participants had to design a model that would predict the behavioral changes that would be observed in the new experiment treatment. We compared the models on their assumptions about speed, direction, and harvesting decisions agents make. All the submitted models underestimated the amount of resources harvested. The best performing model was the simplest model submitted and had the best fit with the original dataset provided.

Keywords: Pattern-Oriented Modeling, Competition, Calibration, Empirical Data, Behavioral Experiments

It is often assumed that irrigation systems require a central authority to solve coordination problems due to the asymmetry in position and influence between those located at the head-end of a system and those located at the tail-end. However, many examples of complex irrigation systems exist that are self-organized without central coordination. Field experiments on asymmetric commons dilemmas are performed with villagers in rural Colombia and Thailand. Our experiments show that there is a dynamic interaction between equality in the use of the common resource, and the level of the contributions to the creation of a common resource. Inequality in the distribution of benefits in one round triggers lower levels of group contributions, reducing efficiency and triggering even more inequality in contributions and distribution of the resource among players.

The upstream players act as “stationary bandits”. They take more than an equal share of the common resource, but leave sufficient resources for the downstream players to stimulate them to continue their contributions to the public infrastructure.

After 10 rounds, players can vote on one of three allocation rules: equal quota, random and rotating access to appropriation of the resource. The rotating access is most often elected. The resource dynamics in the second part of the experiment depend on the rule elected. With the quota rule, the stationary bandit metaphor is less relevant since taking equal shares of the resource is enforced. With the rotation access rule, the players act strategically on the rotating position. They invest more when having the first access to the resource compared to less favorable access. And when they have first access they extract the main part of the common resource. The rotation rule led to a reduction of the performance of the groups. With the random access rule there is no such strategic investment behavior and participants remain investing equal and similar levels as in the first 10 rounds.

The experiments show that a necessary condition of irrigation systems to self-organize is the development of norms to allocate fair shares of the water in order to recruit sufficient labor to construct and maintain the physical infrastructure. The different allocation rules do not increase efficiency, but they did increase equality of the earnings.

Keywords: Field experiments; Irrigation; Common pool resources; Asymmetry; Trust

Field experiments with asymmetric commons dilemmas have shown that groups who are able to derive high social efficiency also had higher equity compared to groups who were not able to derive significant levels of social efficiency. These findings resemble the high productivity in long-lasting irrigation systems based on self-governance. We present an agent-based model based on cultural group selection that shows that the patterns observed in the field experiments can be evolved in cases where agents participate regularly in less challenging symmetric public good dilemmas. These results indicate that cooperation in asymmetric dilemmas can evolve and persist when the agents contend with other social dilemmas than the asymmetric dilemmas.

Keywords: Common pool resources; Equity; Asymmetry; Field experiments; Agent-based; Modeling

In this paper, we discuss the lessons learned from a project that combined different types of methods to study the interaction of ecological dynamics, experience of resource users, and institutional arrangements. We combined theoretical computational models, laboratory experiments with undergraduate students in the USA, field experiments and role games with villagers in rural Thailand and Colombia. The expectation at the start of the project was that specific experience with resource management would affect the way participants play the game and the rules they would develop. We found that contextual variables, such as trust in other community members and the feeling of being an accepted member of the community, and also the ecological context had significant explanatory power, more than experience. Another conclusion from using these different methods is the fact that the quality of resource management lies more on the possibility of communication rather than on the types of rules crafted or selected.

Keywords: Colombia; Thailand; role-playing games; fishery; forestry; irrigation; laboratory experiments; field experiments

In this paper, we discuss laboratory experiments that address the problem of self-governance in an asymmetric commons dilemma. Small-scale irrigation systems that provide food for hundreds of millions of people around the world are probably the most common example of such dilemmas. Here, we formulate an abstract dilemma in which subjects make both a decision about investment in the provision of the infrastructure associated with the use of a resource and about how much to extract from the common-pool resource made available by this infrastructure. The impact of inherent asymmetry in irrigation systems on the provision of a resource and the impact of communication on the capacity of the group to solve the two-level commons dilemma of cooperation and coordination based on the analysis of the experimental data are discussed.

Keywords: Common-pool resources; Asymmetry; Irrigation; Fairness; Real-time experiment

Globalization increases the vulnerability of traditional social-ecological systems (SES) to the incursion of new resource appropriators, i.e. intruders. New external disturbances that increase the physical and socio-political accessibility of SES (e.g. construction of a new road) and weak points in institutional SES of valuable common-pool resources are some of the main factors that enhance the encroachment of intruders. The irrigation system of the northwest Murcia Region (Spain) is an example used in this article of the changes in the structure and robustness of a traditional SES as a result of intruders. In this case study, farmers have traditionally used water from springs to irrigate their lands but, in recent decades, large agrarian companies have settled in this region, using groundwater to irrigate new lands. This intrusion had caused the levels of this resource to drop sharply. In an attempt to adapt, local communities are intensifying the use of resources and are constructing new physical infrastructures; consequently, new vulnerabilities are emerging. This situation seems to be heading toward the inevitably collapse of this traditional SES. From an institutional viewpoint, some recommendations are offered to enhance the robustness of SES in order to mitigate the consequences of intruders.

Keywords: Adaptability, common-pool resources, globalization, groundwater, institutions, resilience, water management

During the last decade, field experiments regarding the study of common pool resource governance have been performed that replicated earlier findings of laboratory experiments. One of the questions is how the decisions made by participants in rural communities are influenced by their experience. This paper presents the results of field experiments in Colombia and Thailand on fishery resources. Context information is derived from the communities via in-depth interviews, surveys and role playing exercises. The use of different methodological tools allowed to link decisions in field experiments with contextual variables for two fishery villages. Explanation of core variables in social dilemmas is given, the degree of cooperation levels, preferred rules, rule compliance and enforcement. Main findings include: i) fishermen made decisions in the field experiments that reflected their own experience and context, ii) agreements for rule crafting are possible only under specific conditions that guarantees livelihoods and sustainability, iii) the broader context determines cooperation levels at a local level, iv) inequalities in the sanctioning of rule breakers decrease the possibilities of reaching cooperation agreements, and v) high levels of trust among local fishermen is not a sufficient condition for resource sustainability, when trust in external rule makers and enforcers is low.

Keywords: Field experiments; Role games; Fisheries; Rules; Cooperation; Trust

The emergence of large-scale irrigation systems has puzzled generations of social scientists, since they are particularly vulnerable to selfish rational actors who might exploit inherent asymmetries in the system (e.g. simply being the head-ender) or who might free ride on the provision of public infrastructure. As part of two related research projects that focus on how subtle social and environmental contextual variables affect the evolution and performance of institutional rules, several sets of experiments have been performed in laboratory settings at Arizona State University and in field settings in rural villages in Thailand and Colombia. In these experiments, participants make both a decision about how much to invest in public infrastructure and how much to extract from the resources generated by that public infrastructure. With both studies we find that head-enders act as stationary bandits. They do take unequal shares of the common-pool resource but if their share is very large relative to downstream participants’ shares, the latter will revolt. Therefore for groups to be successful, head-enders must restrain themselves in their use of their privileged access to the common-pool resource. The comparative approach shows that this result is robust across different social and ecological contexts.

Keywords: Common pool resources; Experimental economics; Asymmetry; Irrigation

Common pool resource experiments in the laboratory and the field have provided insights that have contrasted to those derived from conventional non-cooperative game theory. Contrary to predictions from non-cooperative game theory, participants are sometimes willing to restrain voluntarily from over extracting resources and use costly punishment to sanction other participants. Something as simple as face-to-face communication has been shown to increase average earnings significantly. In the next generation of experiments, both in the laboratory and in the field, we need to extract more information that provides insight concerning why people make the decisions they make. More information is needed concerning attributes of individuals as well as the social and social–ecological context in which they interact that may give rise to such deviations from theoretical predictions. In the process of extracting more information from participants and the contexts in which they interact, we face several methodological and ethical challenges which we address in this paper.

Keywords: Common pool resources; Collective action; Experimental economics; Methodology; Context

For many consumer goods, the advent of online markets dramatically increases the amount of information available about products’ different features and qualities. Although numerous studies have investigated the effects of information quantity on individual-level decisions, it is still unknown how the amount of attribute information affects group-level patterns of behavior, particularly when consumers are also aware of a choice’s popularity. In the present studies, we hypothesized that when attribute information increases, it may exceed the individual’s cognitive capacity to process this information, and as a result conformity – choosing the most popular item – becomes more likely. In this study, we first examined empirical data collected from human subject experiments in a simulated online shopping experience, and then developed an agent-based model (ABM) to explore this behavioral clustering. Both studies confirmed our primary hypotheses, and the ABM shows promise as a tool for exploring extensions of these ideas.

Keywords: Consumer behavior; Decision making; Cognitive processes; Computer simulation

The Global Drylands Observing System proposed in this issue should reduce the huge uncertainty about the extent of desertification and the rate at which it is changing, and provide valuable information to scientists, planners and policy-makers. However, it needs careful design if information outputs are to be scientifically credible and salient to the needs of people living in dry areas. Its design would benefit from a robust, integrated scientific framework like the Dryland Development Paradigm to guide/inform the development of an integrated global monitoring and assessment programme (both directly and indirectly via the use of modelling). Various types of dryland system models (e.g. environmental, socioeconomic, land-use cover change, and agent-based) could provide insights into how to combine the plethora of monitoring information gathered on key socioeconomic and biophysical indicators to develop integrated assessment models. This paper shows how insights from models can help in selecting and integrating indicators, interpreting synthetic trends, incorporating cross-scalar processes, representing spatio-temporal variation, and evaluating uncertainty. Planners could use this integrated global monitoring and assessment programme to help implement effective policies to address the global problem of desertification.

This paper presents a framework for the study of policy implementation in highly uncertain natural resource systems in which uncertainty cannot be characterized by probability distributions. We apply the framework to parametric uncertainty in the traditional Gordon–Schaefer model of a fishery to illustrate how performance can be sacrificed (traded-off) for reduced sensitivity and hence increased robustness, with respect to model parameter uncertainty. With sufficient data, our robustness–vulnerability analysis provides tools to discuss policy options. When less data are available, it can be used to inform the early stages of a learning process. Several key insights emerge from this analysis: (1) the classic optimal control policy can be very sensitive to parametric uncertainty, (2) even mild robustness properties are difficult to achieve for the simple Gordon–Schaefer model, and (3) achieving increased robustness with respect to some parameters (e.g., biological parameters) necessarily results in increased sensitivity (decreased robustness) with respect to other parameters (e.g., economic parameters). We thus illustrate fundamental robustness–vulnerability trade-offs and the limits to robust natural resource management. Finally, we use the framework to explore the effects of infrequent sampling and delays on policy performance.

Keywords: Resource management; Uncertainty; Robust control; Policy implementation; Learning; Vulnerability

Landscapes are increasingly fragmented, and conservation programs have started to look at network approaches for maintaining populations at a larger scale. We present an agent-based model of predator–prey dynamics where the agents (i.e. the individuals of either the predator or prey population) are able to move between different patches in a landscaped network. We then analyze population level and coexistence probability given node-centrality measures that characterize specific patches. We show that both predator and prey species benefit from living in globally well-connected patches (i.e. with high closeness centrality). However, the maximum number of prey species is reached, on average, at lower closeness centrality levels than for predator species. Hence, prey species benefit from constraints imposed on species movement in fragmented landscapes since they can reproduce with a lesser risk of predation, and their need for using anti-predatory strategies decreases.

Keywords: Networks; Landscape; Predator–prey; Coexistence; Survival probabilities; ABM; IBM

Shedding-type of card games are used as a fruit fly to study the evolution of institutional arrangements. Eleven types of rules are identified which leads to a spectrum of 2048 possible shedding games. Each game can be evaluated by the length and difficulty of the game and as such a fitness landscape of possible shedding games can be constructed. Building on cultural group selection simulations are performed with 100 groups which start with randomly throwing cards and evolving to games similar to UNO. Finally, experiments have been performed where characteristics of agents co-evolve with the rules of the game.

Keywords: Institutions; card games; evolution of rules

Human societies have adapted to spatial and temporal variability, such as that found in the prehistoric American Southwest. A question remains as to what the implications are of different social adaptations to the long-term vulnerability of small-scale human societies. A stylized agent-based model is presented that captures small-group decision making on movements and resource use in ancient arid environments. The impact of various assumptions concerning storage, exchange, sharing, and migration on indicators of aggregation and sustainability are explored. Climate variability is found to increase the resilience of population levels at the system level. Variability reduces the time a population stays in one location and can degrade the soils. In addition to climate variability, the long-term population dynamics is mainly driven by the level of storage and the decision rules governing when to migrate and with whom to exchange.

Keywords: agent-based model; archaeology; arid landscapes; climate variability

Case-study analysis shows that long-lasting social–ecological systems have institutional arrangements regulating where, when, and how to appropriate resources instead of how much. Those cases testify to the importance of the fit between ecological and institutional dynamics. Experiments are increasingly used to study decision making, test alternative behavioral models, and test policies. In typical commons dilemma experiments, the only possible decision is how much to appropriate. Therefore, conventional experiments restrict the option to study the interplay between ecological and institutional dynamics. Using a new real-time, spatial, renewable resource environment, we can study the informal norms that participants develop in an experimental resource dilemma setting. Do ecological dynamics affect the institutional arrangements they develop? We find that the informal institutions developed on when, where, and how to appropriate the resource vary with the ecological dynamics in the different treatments. Finally, we find that the amount and distribution of communication messages and not the content of the communication explains the differences between group performances.

Keywords: common-pool resources; communication; institutional innovation; laboratory experiments; problem of fit

Governance of social-ecological systems is a major policy problem of the contemporary era. Field studies of fisheries, forests, and pastoral and water resources have identified many variables that influence the outcomes of governance efforts. We introduce an experimental environment that involves spatial and temporal resource dynamics in order to capture these two critical variables identified in field research. Previous behavioral experiments of commons dilemmas have found that people are willing to engage in costly punishment, frequently generating increases in gross benefits, contrary to game-theoretical predictions based on a static pay-off function. Results in our experimental environment find that costly punishment is again used but lacks a gross positive effect on resource harvesting unless combined with communication. These findings illustrate the importance of careful generalization from the laboratory to the world of policy.

Innovation diffusion theory suggests that consumers differ concerning the number of contacts they have and the degree and the direction to which social influences determine their choice to adopt. To test the impacts of these factors on innovation diffusion, in particular the occurrence of hits and flops, a new agent-based model for innovation diffusion is introduced. This model departs from existing percolation models by using more realistic agents (both individual preferences and social influence) and more realistic networks (scale free with cost constraints). Furthermore, it allows consumers to weight the links they have, and it allows links to be directional. In this way this agent-based model tests the effect of VIPs who can have a relatively large impact on many consumers. Results indicate that markets with high social influence are more uncertain concerning the final success of the innovation and that it is more difficult for the innovation to take off. As consumers affect each other to adopt or not at the beginning of the diffusion, the new product has more difficulties to reach the critical mass that is necessary for the product to take off. In addition, results of the simulation experiments show under which conditions highly connected agents (VIPs) determine the final diffusion of the innovation. Although hubs are present in almost any network of consumers, their roles and their effects in different markets can be very different. Using a scale-free network with a cut-off parameter for the maximum number of connections a hub can have, the simulation results show that when hubs have limits to the maximum number of connections the innovation diffusion is severely hampered, and it becomes much more uncertain. However, it is found that the effect of VIPs on the diffusion curve is often overestimated. In fact when the influence of VIPs on the decision making of the consumers is strengthened compared with the influence of normal friends, the diffusion of the innovation is not substantially facilitated. It can be concluded that the importance of VIPs resides in their capacity to inform many consumers and not in a stronger persuasive power.

A major challenge in the development of computational models of collective behavior is the empirical validation. Experimental data from a spatially explicit dynamic commons dilemma experiment is used to empirically ground an agent-based model. Three distinct patterns are identified in the data. Two naïve models, random walk and greedy agents, do not produce data that match the patterns. A more comprehensive model is presented that explains how participants make movement and harvest decisions. Using pattern-oriented modeling the parameter space is explored to identify the parameter combinations that meet the three identified patterns. Less than 0.1% of the parameter combinations meet all the patterns. These parameter settings were used to successfully predict the patterns of a new set of experiments.

Keywords: empirically grounded agent-based modeling; commons dilemma; individual decision making; human experiments

A replication and analysis of the Artificial Anasazi model is presented. It is shown that the success of replicating historical data is based on two parameters that adjust the carrying capacity of the Long House Valley. Compared to population estimates equal to the carrying capacity the specific agent behavior contributes only a modest improvement of the model to fit the archaeological records.

Keywords: Replication, Model Analysis, Model-Based Archaeology, Population Dynamics, Social-Ecological Systems

With the Internet has come the phenomenon of people volunteering to work on digital public goods such as open source software and online encyclopedia articles. Presumably, the success of individual public goods has an effect on attracting volunteers. However, the definition of success is ill-defined. This paper explores the impact of different success metrics on a simple public goods model. The findings show that the different success metrics considered do have an impact on the behavior of the model, with the largest differences being between consumeroriented and producer-oriented metrics. This indicates that many proposed success metrics may be mapped into one of these two categories and within a category, all success metrics measure the same phenomenon.We argue that the characteristics of produceroriented metrics more closely match real world phenomena, indicating that public goods are driven by producer, and not consumer, interests.

Keywords: Digital public goods, success metrics, FLOSS, open source software, Wikipedia