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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.
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 (Li), which measures the average number of steps a random walker takes to reach the ith node. It is observed that Li is related with the clicks (Ci) to news stories and the age (Ti) 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 main stream 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 of China and USA. It shows that people intrinsically have goodness and social thinking, and can provide public goods voluntarily and have fair preference of economic interest distribution. However, the American students show higher trust degree and cooperation level, and stronger preferences of cooperation and fairness than the Chinese ones. Therefore, this paper suggests that policy makers are necessary to fully understand people’s social thinking and micro behavior and they are necessary to emphasize on publicizing this kind of thinking, ability and action, and should provide 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, 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 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 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
While research-article impact is routinely judged by citation counts, there is recognition that a much broader view is needed to better judge the true value of citations. This paper applies a developing framework based on the application of network theory, where the network consists of journal articles on arid-systems research which are listed on ISI Web-of-Science. Keywords were used to identify articles related to arid-systems research. Linkages between articles were defined by citations, and we bound our analysis by focusing on how the Australian subsample contributes to the international arid-systems literature. The analysis showed that impact based on how articles contribute structurally to the flow of knowledge within the literature offers an alternative metric to citation counts. The analysis also presented a partitioned view of the Australian arid literature. This showed that there exists some citation-based structure within the literature, and we showed this structure better describes the literature than a partition based on which journal articles are published in.
Keywords: Bibliometrics; Dryland; Graph theory; Rangeland; Semiarid
How do groups of social agents organize themselves to cope with stress and disturbances? We address this question by looking at ant colonies. We review the suites of traits that allow ant species to adapt to different disturbance and stress regimes, and changes in these regimes. Low temperatures and low nest site and food resource availability are important stresses that affect ant abundance and distribution. Large-scale habitat disturbances, such as fire, grazing and mining, and small-scale disturbances that more directly affect individual colonies, such as predation, parasitism and disease, also affect ant abundance and distribution. We use functional groups to study the social and individual traits underlying different responses to temperature stress, large-scale habitat disturbance and competition from other ants. Specific individual and colony traits, such as colony size, queen number and worker specialization, seem to underlie adaptation to various stress and disturbance regimes.
The last few years have seen a rapid increase in the number of Free/Libre Open Source Software (FLOSS) projects. Some of these projects, such as Linux and the Apache web server, have become phenomenally successful. However, for every successful FLOSS project there are dozens of FLOSS projects which never succeed. These projects fail to attract developers and/or consumers and, as a result, never get off the ground. The aim of this research is to better understand why some FLOSS projects flourish while others wither and die. This article presents a simple agent-based model that is calibrated on key patterns of data from SourceForge, the largest online site hosting open source projects. The calibrated model provides insight into the conditions necessary for FLOSS success and might be used for scenario analysis of future developments of FLOSS.
Ethnohistory, genetics and simulation are used to propose a new ‘budding model’ to describe the historical processes by which complex irrigation communities may come into existence. We review two alternative theories, Wittfogel’s top-down state-formation theory and common-pool resource management, and suggest that a budding model would better account for existing archaeological and ethnographic descriptions of a well-studied network of irrigation communities on the island of Bali. The budding model is supported by inscriptions and ethnohistorical documents describing irrigation works in and around the drainage of the Petanu River, an area with some of the oldest evidence for wet-rice agriculture in Bali. Genetic analysis of Y-STR and mtDNA shows correlated demographic histories and decreased diversity in daughter villages, consistent with the budding model. Simulation results show that the network of irrigation communities can effectively adjust to repeated budding events that could potentially shock the system outside the parameter space where good harvests can be maintained. Based on this evidence we argue that the budding model is a robust explanation of the historical processes that led to the emergence and operation of Petanu irrigation communities.
Keywords: Bali, irrigation, genetics, pre-colonial, inscriptions, complex adaptive systems
Using a real-time, spatial, renewable resource environment, we observe participants in a set of experiments formulating informal rules during communication sessions over three decision rounds. In all three rounds, the resource is open access. Without communication, the resource is persistently and rapidly depleted. With face-to-face communication, we observe informal arrangements to divide up space and slow down the harvesting rate in various ways. We observe that experienced participants, who have participated in an earlier experiment where private property was used as one way of controlling harvesting in this renewable resource environment, are more effective in creating rules, although they mimic the private-property regime of their prior experience. Inexperienced participants need an extra round to reach the same level of resource use, but they craft diverse arrays of novel rule sets.
Keywords: common-pool resources; laboratory experiments; communication; institutional innovation
Altruistic punishment is suggested to explain observed high levels of cooperation among non-kin related humans. However, laboratory experiments as well as ethnographic evidence suggest that people might retaliate if being punished, and that this reduces the level of cooperation. Building on existing models on the evolution of cooperation and altruistic punishment, we explore the consequences of the option of retaliation. We find that cooperation and altruistic punishment does not evolve with larger population levels if the option of retaliation is included.
Keywords: Public good games; Group selection
This paper uses laboratory experiments to examine the effect of an endogenous rule change from open access to private property as a potential solution to overharvesting in commons dilemmas. A novel, spatial, real-time renewable resource environment was used to investigate whether participants were willing to invest in changing the rules from an open access situation to a private property system. We found that half of the participants invested in creating private property arrangements. Groups who had experienced private property in the second round of the experiment, made different decisions in the third round when open access was reinstituted in contrast to groups who experienced three rounds of open access. At the group level, earnings increased in Round 3, but this was at a cost of more inequality. No significant differences in outcomes occurred between experiments where rules were imposed by the experimental design or chosen by participants.
Keywords: system resources, theoretical analysis, Common-pool resources, institutional change, laboratory experiments, open access, private property
Agent-based modelling has become an increasingly important tool for scholars studying social and social-ecological systems, but there are no community standards on describing, implementing, testing and teaching these tools. This paper reports on the establishment of the Open Agent-Based Modelling Consortium, www.openabm.org, a community effort to foster the agent-based modelling development, communication, and dissemination for research, practice and education.
Keywords: Replication, Documentation Protocol, Software Development, Standardization, Test Beds, Education, Primitives
This article explores the conditions under which agents will cooperate in one-shot two-player Prisoner’s Dilemma games if they are able to withdraw from playing the game and can learn to recognize the trustworthiness of their opponents. When the agents display a number of symbols and they learn which symbols are important to estimate the trustworthiness of others, agents will evolve who cooperate in games in line with experimental observations. These results are robust to significant levels of mutations and errors made by the players.
Keywords: Estimating trustworthiness; Cooperation; One-shot Prisoner’s Dilemma
In this paper we present results of an agent-based model of foraging of hominids. The model represents foraging activities in a landscape that is based on detailed measurements of food availability in the modern East African environ- ments. These current landscapes are used as a model for the environment of the hominids one million years ago. We use the model to explore possible rankings of food preferences for different types of hominids (Homo ergaster and Australo- pithecus boisei) in different types of semi-arid landscapes. We let the agents adjust their preferences to maximize their calories intake and show that A. boisei could not meet its calories requirements in different landscapes.
The governance of common-pool resources can be meaningfully examined from the somewhat broader perspective of the governance of social-ecological systems (SESs). Governance of SESs invariably involves trade-offs; trade-offs between different stakeholder objectives, trade-offs between risk and productivity, and trade-offs between short-term and long-term goals. This is especially true in the case of robustness in social-ecological systems – i.e. the capacity to continue to meet a performance objective in the face of uncertainty and shocks. In this paper we suggest that effective governance under uncertainty must include the ongoing analysis of trade-offs between robustness and performance, and between investments in robustness to different types of perturbations. The nature of such trade-offs will depend on society’s perception of risk, the dynamics of the underlying resource, and the governance regime. Specifically, we argue that it is impossible to define robustness in absolute terms. The choice for society is not only whether to invest in becoming robust to a particular disturbance, but rather, what suit of disturbances to address and what set of associated vulnerabilities is it willing to accept as a necessary consequence.
Keywords: resilience, robustness, social-ecological system, common-pool resources, trade-offs, irrigation
A critical challenge faced by sustainability science is to develop strategies to cope with highly uncertain social and ecological dynamics. This article explores the use of the robust control framework toward this end. After briefly outlining the robust control framework, we apply it to the traditional Gordon–Schaefer fishery model to explore fundamental performance–robustness and robustness–vulnerability trade-offs in natural resource man- agement. We find that the classic optimal control policy can be very sensitive to parametric uncertainty. By exploring a large class of alternative strategies, we show that there are no panaceas: even mild robustness properties are difficult to achieve, and increasing robustness to some parameters (e.g., biological parameters) results in decreased robustness with respect to others (e.g., economic parameters). On the basis of this example, we extract some broader themes for better management of resources under uncer- tainty and for sustainability science in general. Specifically, we focus attention on the importance of a continual learning process and the use of robust control to inform this process.
Keywords: natural resources; resource management; vulnerability; policy design; environmental policy
In the context of governance of human–environment interactions, a panacea refers to a blueprint for a single type of governance system (e.g., government ownership, privatization, community property) that is applied to all environmental problems. The aim of this special feature is to provide theoretical analysis and empirical evidence to caution against the tendency, when confronted with pervasive uncertainty, to believe that scholars can generate simple models of linked social–ecological systems and deduce general solutions to the overuse of resources. Practitioners and scholars who fall into panacea traps falsely assume that all problems of resource governance can be represented by a small set of simple models, because they falsely perceive that the preferences and perceptions of most resource users are the same. Readers of this special feature will become acquainted with many cases in which panaceas fail. The articles provide an excellent overview of why they fail. Furthermore, the articles in this special feature address how scholars and public officials can increase the prospects for future sustainable resource use by facilitating a diagnostic approach in selecting appropriate starting points for governance and monitoring, as well as by learning from the outcomes of new policies and adapting in light of effective feedback.
Keywords: resources; social–ecological systems; sustainability
In Janssen et al. (2006), we presented a bibliometric analysis of the resilience, vulnerability, and adaptation knowledge domains within the research activities on human dimensions of global environmental change. We have updated the analysis because 2 years have gone by since the original analysis, and 1113 more publications can now be added to the database. We analyzed how the resulting 3399 publications between 1967 and 2007 are related in terms of co-authorship and citations. The rapid increase in the number of publications in the three knowledge domains continued over the last 2 years, and we still see an overlap between the knowledge domains. We were also able to identify the “hot” publications of the last 2 years.
Keywords: adaptation; bibliometric analysis; citations; resilience; vulnerability
Deforestation often has been studied in terms of land-use models, in which natural processes such as ecological succession, physical disturbance and human decision-making are combined. In many land-use models, landowners are assumed to make decisions that maximize their utilities. However, since human understanding of ecological and social dynamics is clouded by uncertainty, landowners may not know true utility values, and may learn these values from their experiences. We develop a decision model for forest use under social learning to explore whether social learning is efficient to improve landowners’ decisions and can lead to effective forest management. We assume that a forest is composed of a number of land parcels that are individually managed; landowners choose whether or not to cut trees by comparing the expected utilities of forest conservation and deforestation; landowners learn utility values not only from their own experiences, but also by exchanging and sharing information with others in a society. By analyzing the equilibrium and stability of the landscape dynamics, we observed four possible outcomes: a stationary-forested landscape, a stationary-deforested landscape, an unstable landscape fluctuating near an equilibrium, and a cyclic-forested landscape induced by synchronized deforestation. Synchronized deforestation, which resulted in a resource shortage in a society, was likely to occur when landowners employed a stochastic decision and a short-term memory about past experiences. Social welfare under a cyclic-forested landscape can be significantly lower than that of a stationary-forested landscape. This implies that learning and remembering past experiences are crucial to prevent overexploitation of forest resources and degradation of social welfare.
Keywords: Decision-making; Expected utility; Slow regeneration; Memory; Markov chain; Stochastic decision
Many marketing efforts focus on promotional activities that support the launch of new products. Promotional strategies may play a crucial role in the early stages of the product life cycle, and determine to a large extent the diffusion of a new product. This paper proposes an agent-based model to simulate the efficacy of different promotional strategies that support the launch of a product. The article in particular concentrates on the targeting and the timing of the promotions. The results of the simulation experiments indicate that promotional activities highly affect diffusion dynamics. The findings indicate that: (1) the absence of promotional support and/or a wrong timing of the promotions may lead to a failure of product diffusion; (2) the optimal targeting strategy is to address distant, small and cohesive groups of consumers; and (3) the optimal timing of a promotion differs between durable categories (white goods, such as kitchens and laundry machines, versus brown goods, such as TVs and CDs players). These results contribute to the planning and the management of promotional strategies supporting new product launches.
Keywords: Diffusion of innovations; Agent-based model; Targeting strategies; Promotions; Takeoff of diffusions; Word-of-mouth; Social influence
The use of agent-based models (ABMs) for investigating land-use science questions has been increasing dramatically over the last decade. Modelers have moved from ‘proofs of existence’ toy models to case-specific, multi-scaled, multi-actor, and data-intensive models of land-use and land-cover change. An international workshop, titled ‘Multi-Agent Modeling and Collaborative Planning—Method2Method Workshop’, was held in Bonn in 2005 in order to bring together researchers using different data collection approaches to informing agent-based models. Participants identified a typology of five approaches to empirically inform ABMs for land use science: sample surveys, participant observation, field and laboratory experiments, companion modeling, and GIS and remotely sensed data. This paper reviews these five approaches to informing ABMs, provides a corresponding case study describing the model usage of these approaches, the types of data each approach produces, the types of questions those data can answer, and an evaluation of the strengths and weaknesses of those data for use in an ABM.
Keywords: agent-based model, empirical parameterization, human–environment interactions, household surveys, experiments, companion modeling, participant observation, spatial data
Diffusions of new products and technologies through social networks can be formalized as spreading of infectious diseases. However, while epidemiological models describe infection in terms of transmissibility, we propose a diffusion model that explicitly includes consumer decision-making affected by social influences and word-of-mouth processes. In our agent-based model consumers’ probability of adoption depends on the external marketing effort and on the internal influence that each consumer perceives in his/her personal networks. Maintaining a given marketing effort and assuming its effect on the probability of adoption as linear, we can study how social processes affect diffusion dynamics and how the speed of the diffusion depends on the network structure and on consumer heterogeneity. First, we show that the speed of diffusion changes with the degree of randomness in the network. In markets with high social influence and in which consumers have a sufficiently large local network, the speed is low in regular networks, it increases in small-world networks and, contrarily to what epidemic models suggest, it becomes very low again in random networks. Second, we show that heterogeneity helps the diffusion. Ceteris paribus and varying the degree of heterogeneity in the population of agents simulation results show that the more heterogeneous the population, the faster the speed of the diffusion. These results can contribute to the development of marketing strategies for the launch and the dissemination of new products and technologies, especially in turbulent and fashionable markets.
Keywords: Innovation diffusion; Threshold models; Word-of-mouth; Social networks; Heterogeneous markets
Some social-ecological systems (SESs) have persisted for hundreds of years, remaining in particular configurations that have withstood a variety of natural and social disturbances. Many of these long-lived SESs have adapted their institutions to the particular pattern of variability they have experienced over time as well as to the broader economic, political, and social system in which they are located. Such adaptations alter resource use patterns in time and/or space to maintain the configuration of the SESs. Even well-adapted SESs, however, can become vulnerable to new types of disturbances. Through the analysis of a series of case studies, we begin to characterize different types of adaptations to particular types of variability and explore vulnerabilities that may emerge as a result of this adaptive process. Understanding such vulnerabilities may be critical if our interest is to contribute to the future adaptations of SESs as the more rapid processes of globalization unfold.
Keywords: disturbances, institutions, resilience, robustness, social-ecological system, variability
Farmers within irrigation systems, such as those in Bali, solve complex coordination problems to allocate water and control pests. Lansing and Kremer’s [Lansing, J.S., Kremer, J.N., 1993. Emergent properties of Balinese water temples. American Anthropologist 95(1), 97–114] study of Balinese water temples showed that this coordination problem can be solved by assuming simple local rules for how individual communities make their decisions. Using the original Lansing–Kremer model, the robustness of their insights was analyzed and the ability of agents to self-organize was found to be sensitive to pest dynamics and assumptions of agent decision making.
Keywords: Irrigation; Coordination; Networks; Synchronization; Agent-based model
Social-ecological systems are complex adaptive systems where social and biophysical agents are interacting at multiple temporal and spatial scales. The main challenge for the study of governance of social-ecological systems is improving our understanding of the conditions under which cooperative solutions are sustained, how social actors can make robust decisions in the face of uncertainty and how the topology of interactions between social and biophysical actors affect governance. We review the contributions of agent-based modeling to these challenges for theoretical studies, studies which combines models with laboratory experiments and applications of practical case studies. Empirical studies from laboratory experiments and field work have challenged the predictions of the conventional model of the selfish rational agent for common pool resources and public-good games. Agent-based models have been used to test alternative models of decision-making which are more in line with the empirical record. Those models include bounded rationality, other regarding preferences and heterogeneity among the attributes of agents. Uncertainty and incomplete knowledge are directly related to the study of governance of social-ecological systems. Agent-based models have been developed to explore the consequences of incomplete knowledge and to identify adaptive responses that limited the undesirable consequences of uncertainties. Finally, the studies on the topology of agent interactions mainly focus on land use change, in which models of decision-making are combined with geographical information systems. Conventional approaches in enviromental economics do not explicitly include non-convex dynamics of ecosystems, non-random interactions of agents, incomplete understanding, and empirically based models of behavior in collective action. Although agent-based modeling for social-ecological systems is in its infancy, it addresses the above features explicitly and is therefore potentially useful to address the current challenges in the study of governance of social-ecological systems.
There is an increasing drive to combine agent-based models with empirical methods. An overview is provided of the various empirical methods that are used for different kinds of questions. Four categories of empirical approaches are identified in which agent-based models have been empirically tested: case studies, stylized facts, role-playing games, and laboratory experiments. We discuss how these different types of empirical studies can be combined. The various ways empirical techniques are used illustrate the main challenges of contemporary social sciences: (1) how to develop models that are generalizable and still applicable in specific cases, and (2) how to scale up the processes of interactions of a few agents to interactions among many agents.
Keywords: Agent-based models; empirical applications; social science methods
This study compares the empirical performance of a variety of learning models and theories of social preferences in the context of experimental games involving the provision of public goods. Parameters are estimated via maximum likelihood estimation. We also performed estimations to identify different types of agents and distributions of parameters. The estimated models suggest that the players of such games take into account the learning of others and are belief learners. Despite these interesting findings, we conclude that a powerful method of model selection of agent-based models on dynamic social dilemma experiments is still lacking.
Keywords: laboratory experiments; public goods; agent-based model; learning; social preferences
When the stakes of stakeholders are not properly incorporated during early phases of a planning process, it may later give rise to severe conflicts. The issue of how to deal with stakeholders in regional water management has been a subject of ongoing debate in the Netherlands. This paper promotes a ‘platform’ approach where stakeholders collectively attempt to develop plans for regional water management. Ideas for this platform approach are based on a review of research on groups governing common-pool resources. We argue that simple negotiation and mediation support tools can offer useful support and can serve to facilitate platform negotiations. We present a simple mediation and negotiation tool to support the early phases of such a land use planning process. The tool translates stakeholder preferences on the use of the landscape into spatially explicit value maps. Proposed plans can be evaluated and potential conflicts can be identified. The use of such a tool enables stakeholders and mediators to formulate explicitly the problems that need to be addressed in the decision-making process.
Keywords: Regional water management; Mediation and negotiation support; Spatial conflicts; Platforms for collaborative planning; Participatory approaches; GIS; Decision support
The evolution of cooperation is possible with a simple model of a population of agents that can move between groups. The agents play public good games within their group. The relative fitness of individuals within the whole population affects their number of offspring. Groups of cooperators evolve but over time are invaded by defectors which eventually results in the group’s extinction. However, for small levels of migration and mutation, high levels of cooperation evolve at the population level. Thus, evolution of cooperation based on individual fitness without kin selection, indirect or direct reciprocity is possible. We provide an analysis of the parameters that affect cooperation, and describe the dynamics and distribution of population sizes over time.
Keywords: Evolution of cooperation; Group structure; Public good games
We argue that globalization is a central feature of coupled human–environment systems or, as we call them, socio-ecological systems (SESs). In this article, we focus on the effects of globalization on the resilience, vulnerability, and adaptability of these systems. We begin with a brief discussion of key terms, arguing that socio-economic resilience regularly substitutes for biophysical resilience in SESs with consequences that are often unforeseen. A discussion of several mega-trends (e.g. the rise of mega-cities, the demand for hydrocarbons, the revolution in information technologies) underpins our argument. We then proceed to identify key analytical dimensions of globalization, including rising connectedness, increased speed, spatial stretching, and declining diversity. We show how each of these phenomena can cut both ways in terms of impacts on the resilience and vulnerability of SESs. A particularly important insight flowing from this analysis centers on the reversal of the usual conditions in which large-scale things are slow and durable while small-scale things are fast and ephemeral. The fact that SESs are reflexive can lead either to initiatives aimed at avoiding or mitigating the dangers of globalization or to positive feedback processes that intensify the impacts of globalization. In the concluding section, we argue for sustained empirical research regarding these concerns and make suggestions about ways to enhance the incentives for individual researchers to work on these matters.
Keywords: Globalization; Resilience; Vulnerability; Adaptation; Socio-ecological system
This paper presents the results of a bibliometric analysis of the knowledge domains resilience, vulnerability and adaptation within the research activities on human dimensions of global environmental change. We analyzed how 2286 publications between 1967 and 2005 are related in terms of co-authorship relations, and citation relations.
The number of publications in the three knowledge domains increased rapidly between 1995 and 2005. However, the resilience knowledge domain is only weakly connected with the other two domains in terms of co-authorships and citations. The resilience knowledge domain has a background in ecology and mathematics with a focus on theoretical models, while the vulnerability and adaptation knowledge domains have a background in geography and natural hazards research with a focus on case studies and climate change research. There is an increasing number of cross citations and papers classified in multiple knowledge domains. This seems to indicate an increasing integration of the different knowledge domains.
Keywords: Knowledge domains; Co-authorship networks; Resilience; Vulnerability; Adaptation; Citations; Publications
Institutions, the rules that govern interactions between people, evolve over time. This special issue presents a number of detailed case studies of human–environment interactions during a significant historical period. With social-ecological systems we mean a set of people, their natural and human-made resources, and the relationships among them (Anderies et al., 2004, Janssen et al., 2005).
Many government and private programs provide incentives for non-industrial private forest (NIPF) owners. Due to the complexity of this web of programs, the incentives of the programs are unclear. We focus on four specific programs that represent different rule structures—a federal cost-share program, a state tax incentive program, a nationwide private stewardship program, and a local private conservation organization. We perform institutional analysis of the formal and informal rules of the programs based on literature review, discussions with officers, and formal guidelines of the programs. We classify different types of rule structures, and explain them in relation to goals and organizational structures of the programs.
Keywords: Forest; Government programs; Non-governmental organizations; Institutions
We explore the response of pastoralists to rangeland resource variation in time and space, focusing on regions where high variation makes it unlikely that an economically viable herd can be maintained on a single management unit. In such regions, the need to move stock to find forage in at least some years has led to the evolution of nomadism and transhumance, and reciprocal grazing agreements among the holders of common-property rangeland. The role of such informal institutions in buffering resource variation is well documented in some Asian and African rangelands, but in societies with formally established private-property regimes, where we focus, such institutions have received little attention. We examine agistment networks, which play an important role in buffering resource variation in modern-day Australia. Agistment is a commercial arrangement between pastoralists who have less forage than they believe they require and pastoralists who believe they have more. Agistment facilitates the movement of livestock via a network based largely on trust. We are concerned exclusively with the link between the characteristics of biophysical variation and human aspects of agistment networks, and we developed a model to test the hypothesis that such a link could exist. Our model builds on game theory literature, which explains cooperation between strangers based on the ability of players to learn whom they can trust. Our game is played on a highly stylized landscape that allows us to control and isolate the degree of spatial variation and spatial covariation. We found that agistment networks are more effective where spatial variation in resource availability is high, and generally more effective when spatial covariation is low. Policy design that seeks to work with existing social networks in rangelands has potential, but this potential varies depending on localized characteristics of the biophysical variability.
Increased spatial dependency of economic activities, as well as spatial differentiation of production and consumption, has implications for environmental policy. One of the issues that has gained importance is the responsibility for the emissions from products that cross national boundaries during the environmental policy’s lifetime. This paper discusses the different ethical views of environmental responsibility. Furthermore, the policy measures that are associated with the different viewpoints are analyzed in a novel dynamic two-country two-sector dynamic input–output model. A numerical example is modeled to assess taxing schemes that are based on these ethical viewpoints. The results show that a tax on the ‘embodied’ environmental pressure, which is generally viewed as ethically preferable, is less effective that the current policy of taxing consumers of products. Our discussion however shows that these results are very dependent on the model structure and initial parameters that are used. Nevertheless, the model illustrates that policies that are based on ethically superior standpoints may have detrimental distortionary effects in the dynamic setting.
Keywords: Dynamic input–output model, international trade, technological change, environmental responsibility.
Formal models used to study the resilience of social-ecological systems have not explicitly included important structural characteristics of this type of system. In this paper, we propose a network perspective for social-ecological systems that enables us to better focus on the structure of interactions between identifiable components of the system. This network perspective might be useful for developing formal models and comparing case studies of social-ecological systems. Based on an analysis of the case studies in this special issue, we identify three types of social-ecological networks: (1) ecosystems that are connected by people through flows of information or materials, (2) ecosystem networks that are disconnected and fragmented by the actions of people, and (3) artificial ecological networks created by people, such as irrigation systems. Each of these three archytypal social-ecological networks faces different problems that influence its resilience as it responds to the addition or removal of connections that affect its coordination or the diffusion of system attributes such as information or disease.
Keywords: network topology; resilience; social-ecological systems; social-ecological networks
Reputation systems are used to facilitate interaction between strangers in one-shot social dilemmas, like transactions in e-commerce. The functioning of various reputation systems depend on voluntary feedback derived from the participants in those social dilemmas. In this paper a model is presented under which frequencies of providing feedback to positive and negative experiences in reputation systems explain observed levels of cooperation. The results from simulations show that it is not likely that reputation scores alone will lead to high levels of cooperation.
Keywords: Trust, Reputation, One-Shot Prisoner Dilemma, Voluntary Feedback, Symbols.
This article discusses the evolution of institutional rules, the prescriptions that humans use to shape their collective activities. Four aspects of the rules are discussed: coding, creation, selection, and memory. The immune system provides us a useful metaphor to relate these four aspects into a coherent framework. For each aspect, the relevant dynamics in social systems and immune systems are discussed. Finally, a framework for a computational model to study the evolution of rules is sketched.
Computational models of human collective behavior offer promise in providing quantitative and empirically verifiable accounts of how individual decisions lead to the emergence of group-level organizations. Agent-based models (ABMs) describe interactions among individual agents and their environment, and provide a process-oriented alternative to descriptive mathematical models. Recent ABMs provide compelling accounts of group pattern formation, contagion and cooperation, and can be used to predict, manipulate and improve upon collective behavior. ABMs overcome an assumption that underlies much of cognitive science – that the individual is the crucial unit of cognition. The alternative advocated here is that individuals participate in collective organizations that they might not understand or even perceive, and that these organizations affect and are affected by individual behavior.
How do systems respond to disturbances? The capacity of a system to respond to disturbances varies for different types of disturbance regimes. We distinguish two types of responses: one that enables the system to absorb disturbances from an existing disturbance regime, and one that enables a system to reconstruct itself after a fundamental change in a disturbance regime. We use immune systems as a model for how systems can deal with disturbances, and use this model to derive insights in adaptive capacity of social-ecological systems. We identify a tension between the two types of responses where one benefits from learning and memory while the other requires fast-turnover of experience. We discuss how this may affect building up adaptive capacity of social-ecological systems.
Keywords: disturbance regimeadaptive capacitysocial-ecological systemsimmune systemsresilience
What makes social-ecological systems (SESs) robust? In this paper, we look at the institutional configurations that affect the interactions among resources, resource users, public infrastructure providers, and public infrastructures. We propose a framework that helps identify potential vulnerabilities of SESs to disturbances. All the links between components of this framework can fail and thereby reduce the robustness of the system. We posit that the link between resource users and public infrastructure providers is a key variable affecting the robustness of SESs that has frequently been ignored in the past. We illustrate the problems caused by a disruption in this link. We then briefly describe the design principles originally developed for robust common-pool resource institutions, because they appear to be a good starting point for the development of design principles for more general SESs and do include the link between resource users and public infrastructure providers.
Keywords: institutions, resilience, robustness, social-ecological systems.
What makes social-ecological systems (SESs) robust? In this paper, we look at the institutional configurations that affect the interactions among resources, resource users, public infrastructure providers, and public infrastructures. We propose a framework that helps identify potential vulnerabilities of SESs to disturbances. All the links between components of this framework can fail and thereby reduce the robustness of the system. We posit that the link between resource users and public infrastructure providers is a key variable affecting the robustness of SESs that has frequently been ignored in the past. We illustrate the problems caused by a disruption in this link. We then briefly describe the design principles originally developed for robust common-pool resource institutions, because they appear to be a good starting point for the development of design principles for more general SESs and do include the link between resource users and public infrastructure providers.
Keywords: institutions, resilience, robustness, social-ecological systems.
Savanna rangelands are characterized by dynamic interactions between grass, shrubs, fire and livestock driven by highly variable rainfall. When the livestock are grazers (only or preferentially eating grass) the desirable state of the system is dominated by grass, with scattered trees and shrubs. However, the system can have multiple stable attractors and a perturbation such as a drought can cause it to move from such a desired configuration into one that is dominated by shrubs with very little grass. In this paper, using the rangelands of New South Wales in Australia as an example, we provide a methodology to find robust management strategies in the context of this complex ecological system driven by stochastic rainfall events. The control variables are sheep density and the degree of fire suppression. By comparing the optimal solution where it is assumed the manager has perfect knowledge and foresight of rainfall conditions with one where the rainfall variability is ignored, we found that rainfall variability and the related uncertainty lead to a reduction of the possible expected returns from grazing activity by 33%. Using a genetic algorithm, we develop robust management strategies for highly variable rainfall that more than doubles expected returns compared to those obtained under variable rainfall using an optimal solution based on average rainfall (i.e., where the manager ignores rainfall variability).
Our analysis suggests some key features of a robust strategy. The robust strategy is precautionary and is forced by rainfall variability. It is less reactive with respect to grazing pressure changes and more reactive with respect to fire suppression than is an optimum strategy based on a deterministic system (no rainfall variability). Finally, the costs associated with implementing a robust strategy are far less than the expected economic losses when uncertainty is not taken into account.
Keywords: Rangelands; Multiple stable states; Robust management; Genetic algorithms
Most important environmental problems can be related to materials flows through the economy. Regional and national economies use materials that are either extracted domestically or imported from other regions. Therefore, an analysis of optimal patterns of combined economic development and materials use requires that both trade and environmental aspects are taken into account. A model is presented here that optimises long-term welfare for two regions that trade in virgin and recycled materials as well as consumer goods. The regions differ in one respect, namely with regard to domestic availability of a material resource. Analysis of the model shows, among other things, that the relationship between production and virgin material use can follow an Environmental Kuznets curves or an N-shaped curve. The latter points at “re-linking” of income growth and material resource use. Although trade of material resources and goods increases the carrying capacity of both regions, and in turn their levels of welfare, it can not prevent the re-linking phenomenon.
The use of agent-based modeling (ABM) has recently been extended to the study of natural resource management and land-use and land-cover change. Many ABM applications have been at a conceptual and abstract level, which helps scholars to recognize how macro patterns can emerge from simple rules followed by agents at a micro level. ABM has a greater potential than many other approaches to capture the dynamic relationships between social and ecological systems. This paper contributes to a larger effort to explore how individual decision making by a heterogeneous set of landowners, given local biophysical conditions, led to the particular aggregate pattern of land-cover change in Indiana, with an emphasis on forest-cover change. In our preliminary effort, we created a model structure that allowed examination of the institutional impact of government programs on individual land-use decisions. Our model is based on the concept that an initial condition endows an agent with a particular set of beliefs and desires that could lead to any number of intentions, actions, and outcomes. Institutions have the potential to intervene in an agent’s decision-making process and alter its beliefs and desires by providing information and incentives. The next crucial step in our effort will be to extend this model to study the impact of other political institutions, such as taxation and zoning, as well as utilize the conceptual model to facilitate implementation of institutions in the agent-based model.
Multi agent simulation (MAS) is a tool that can be used to explore the dynamics of different systems. Considering that many demographic phenomena have roots in individual choice behaviour and social interactions it is important that this behaviour is being translated in agent rules. Several behaviour theories are relevant in this context, and hence there is a necessity of using a meta-theory of behaviour as a framework for the development of agent rules. The consumat approach provides a basis for such a framework, as is demonstrated with a discussion of modelling the diffusion of contraceptives. These diffusion processes are strongly influenced by social processes and cognitive strategies. Different possible research lines are discussed which might be addressed with a multi-agent approach like the consumats.
Markets can show different types of dynamics, from quiet markets dominated by one or a few products, to markets with continual penetration of new and reintroduced products. In a previous article we explored the dynamics of markets from a psychological perspective using a multi-agent simulation model. The main results indicated that the behavioral rules dominating the artificial consumer’s decision making determine the resulting market dynamics, such as fashions, lock-in, and unstable renewal. Results also show the importance of psychological variables like social networks, preferences, and the need for identity to explain the dynamics of markets. In this article we extend this work in two directions. First, we will focus on a more systematic investigation of the effects of different network structures. The previous article was based on Watts and Strogatz’s approach, which describes the small-world and clustering characteristics in networks. More recent research demonstrated that many large networks display a scale-free power-law distribution for node connectivity. In terms of market dynamics this may imply that a small proportion of consumers may have an exceptional influence on the consumptive behavior of others (hubs, or early adapters). We show that market dynamics is a self-organized property depending on the interaction between the agents’ decision-making process (heuristics), the product characteristics (degree of satisfaction of unit of consumption, visibility), and the structure of interactions between agents (size of network and hubs in a social network).
This article presents an overview of multi-agent system models of land-use/cover change (MAS/LUCC models). This special class of LUCC models combines a cellular landscape model with agent-based representations of decision making, integrating the two components through specification of interdependencies and feedbacks between agents and their environment. The authors review alternative LUCC modeling techniques and discuss the ways in which MAS/LUCC models may overcome some important limitations of existing techniques. We briefly review ongoing MAS/LUCC modeling efforts in four research areas. We discuss the potential strengths of MAS/LUCC models and suggest that these strengths guide researchers in assessing the appropriate choice of model for their particular research question. We find that MAS/LUCC models are particularly well suited for representing complex spatial interactions under heterogeneous conditions and for modeling decentralized, autonomous decision making. We discuss a range of possible roles for MAS/LUCC models, from abstract models designed to derive stylized hypotheses to empirically detailed simulation models appropriate for scenario and policy analysis. We also discuss the challenge of validation and verification for MAS/LUCC models. Finally, we outline important challenges and open research questions in this new field. We conclude that, while significant challenges exist, these models offer a promising new tool for researchers whose goal is to create fine-scale models of LUCC phenomena that focus on human-environment interactions.
Keywords: agent-based modeling, cellular automata, complexity theory, land-use and land-cover change, multi-agent systems
In this paper we argue that simulating complex systems involving human behaviour requires agent rules based on a theoretically rooted structure that captures basic behavioural processes. Essential components of such a structure involve needs, decision-making processes and learning. Such a structure should be based on state-of-the-art behavioural theories and validated on the micro-level using experimental or field data of individual behaviour. We provide some experiences we had working with such a structure, which involve the possibility to relate the results of simulations on different topics, the ease of building in extra factors for specific research questions and the possibility to use empirical data in calibrating the model. A disadvantage we experienced is the lack of suiting empirical data, which necessitates in our view the combined use of empirical and simulation research.
The Leuser Ecosystem in Northern Sumatra is officially protected by its status as an Indonesian national park. Nevertheless, it remains under severe threat of deforestation. Rainforest destruction has already caused a decline in ecological functions and services. Besides, it is affecting numerous economic activities in and around the Leuser National Park. The objectives of this study are twofold: firstly, to determine the total economic value (TEV) of the Leuser Ecosystem through a systems dynamic model. And secondly, to evaluate the economic consequences of deforestation versus conservation, disaggregating the economic value for the main stakeholders and regions involved. Using a dynamic simulation model, economic valuation is applied to evaluate the TEV of the Leuser National Park over the period 2000–2030. Three scenarios are considered: ‘conservation’, ‘deforestation’ and, ‘selective use’. The results are presented in terms of (1) the type of benefits, (2) the allocation of these benefits among stakeholders, and (3) the regional distribution of benefits. The economic benefits considered include: water supply, fisheries, flood and drought prevention, agriculture and plantations, hydro-electricity, tourism, biodiversity, carbon sequestration, fire prevention, non-timber forest products, and timber. The stakeholders include: local community members, the local government, the logging and plantation industry, the national government, and the international community. The regions considered cover the 11 districts involved in the management of the Leuser Ecosystem. With a 4% discount rate, the accumulated TEV for the ecosystem over the 30-year period is: US $7.0 billion under the ‘deforestation scenario’, US $9.5 billion under the ‘conservation scenario’ and US $9.1 billion under the ‘selective utilisation scenario’. The main contributors in the conservation and selective use scenarios are water supply, flood prevention, tourism and agriculture. Timber revenues play an important role in the deforestation scenario. Compared to deforestation, conservation of the Leuser Ecosystem benefits all categories of stakeholders, except for the elite logging and plantation industry.
Keywords: Natural resource valuation; Conservation; Deforestation; Indonesia
This paper discusses the evolution of rules between people for the management of ecosystems. Four aspects of the rules are discussed: coding, creation, selection and memory. The immune system provides us a useful metaphor to relate these four aspects into a coherent framework. We sketch a framework for a computational model to study the evolution of rules for the management of ecosystems.
An approach is introduced to combine survey data with multi-agent simulation models of consumer behaviour to study the diffusion process of organic food consumption. This methodology is based on rough set theory, which is able to translate survey data into behavioural rules. The topic of rule induction has been extensively investigated in other fields and in particular in learning machine, where several efficient algorithms have been proposed. However, the peculiarity of the rough set approach is that the inconsistencies in a data set about consumer behaviour are not aggregated or corrected since lower and upper approximation are computed. Thus, we expect that rough sets theory is suitable to extract knowledge in the form of rules within a consistent theoretical framework of consumer behaviour.
We report on a series of computer simulation experiments regarding the management of a common resource. We were particularly interested in the effects of uncertainty and satisfaction on the harvesting behaviour of simulated agents. The experimental study of long-term dynamics of threatened resources can hardly be carried out using human subjects. We therefore experimented with simulated consumers, the so-called consumats, whose properties are derived from a comprehensive, multitheoretical model of consumer behaviour. A consumat is equipped with needs and abilities, and may engage in different cognitive processes, such as deliberation, social comparison, imitation, and repetition of previous behaviour. In a first simulation experiment we show as to how uncertainty may stimulate an imitation effect that promotes over-harvesting. In two subsequent series of experiments, we show that increased uncertainty results in an increased ‘optimism’ of consumats regarding future outcomes, an increased likelihood of imitative behaviour, and a lesser adaptation of harvesting behaviour during resource depletion. These ‘process-effects’ promote higher levels of harvesting from a collective resource. The main experimental conclusions and the issue of validating simulation results are discussed.
In this article, we identify four typical roles played by computer models in environmental policy-making, and explore the relationship of these roles to different stages of policy development over time. The four different roles are: models as eye-openers, models as arguments in dissent, models as vehicles in creating consensus and models for management. A general environmental policy life cycle is used to assess the different roles models play in the policy process. The relationship between the roles of models and the different stages of the policy life cycle is explored with a selection of published accounts of computer models and their use in environmental policy-making.
Keywords: Computer models; Environmental policy; Policy life cycle; Policy process
This paper presents a model-based analysis of the introduction of green products, which are products with low environmental impacts. Both consumers and firms are simulated as populations of agents who differ in their behavioural characteristics. Model experiments illustrate the influence of behavioural characteristics on the success of switching to green consumption. The model reproduces empirical observed stylised facts and shows the importance of social processing and status seeking in diffusion processes. The flexibility of firms to adapt to new technology is found to have an important influence on the type of consumers who change their consumption to green products in the early phase of the diffusion process. Keywords: Diffusion processes – Consumer behaviour – Social networks – Service economy
This paper presents a model-based analysis of the introduction of green products, which are products with low environmental impacts. Both consumers and firms are simulated as populations of agents who differ in their behavioural characteristics. Model experiments illustrate the influence of behavioural characteristics on the success of switching to green consumption. The model reproduces empirical observed stylised facts and shows the importance of social processing and status seeking in diffusion processes. The flexibility of firms to adapt to new technology is found to have an important influence on the type of consumers who change their consumption to green products in the early phase of the diffusion process.
Keywords: Diffusion processes – Consumer behaviour – Social networks – Service economy
Approaches to natural resource management are often based on a presumed ability to predict probabilistic responses to management and external drivers such as climate. They also tend to assume that the manager is outside the system being managed. However, where the objectives include long-term sustainability, linked social-ecological systems (SESs) behave as complex adaptive systems, with the managers as integral components of the system. Moreover, uncertainties are large and it may be difficult to reduce them as fast as the system changes. Sustainability involves maintaining the functionality of a system when it is perturbed, or maintaining the elements needed to renew or reorganize if a large perturbation radically alters structure and function. The ability to do this is termed “resilience.” This paper presents an evolving approach to analyzing resilience in SESs, as a basis for managing resilience. We propose a framework with four steps, involving close involvement of SES stakeholders. It begins with a stakeholder-led development of a conceptual model of the system, including its historical profile (how it got to be what it is) and preliminary assessments of the drivers of the supply of key ecosystem goods and services. Step 2 deals with identifying the range of unpredictable and uncontrollable drivers, stakeholder visions for the future, and contrasting possible future policies, weaving these three factors into a limited set of future scenarios. Step 3 uses the outputs from steps 1 and 2 to explore the SES for resilience in an iterative way. It generally includes the development of simple models of the system’s dynamics for exploring attributes that affect resilience. Step 4 is a stakeholder evaluation of the process and outcomes in terms of policy and management implications. This approach to resilience analysis is illustrated using two stylized examples.
We analyse commercially operated rangelands as coupled systems of people and nature. The biophysical components include: (i) the reduction and recovery of potential primary production, re ected as changes in grass production per unit of rainfall; (ii) changes in woody plants dependent on the grazing and re regimes; and (iii) livestock and wool dynamics in uenced by season, condition of the rangeland and numbers of wild and feral animals. The social components include the managers, who vary with regard to a range of cognitive abilities and lifestyle choices, and the regulators who vary in regard to policy goals.
We compare agent-based and optimization models of a rangeland system. The agent-based model leads to recognition that policies select for certain management practices by creating a template that governs the trajectories of the behaviour of individuals, learning, and overall system dynamics. Conservative regu- lations reduce short-term loss in production but also restrict learning. A free-market environment leads to severe degradation but the surviving pastoralists perform well under subsequent variable conditions. The challenge for policy makers is to balance the needs for learning and for preventing excessive degra- dation. A genetic algorithm model optimizing for net discounted income and based on a population of management solutions (stocking rate, how much to suppress re, etc.) indicates that robust solutions lead to a loss of about 40% compared with solutions where the sequence of rainfall was known in advance: this is a similar gure to that obtained from the agent-based model.
We conclude that, on the basis of Levin’s three criteria, rangelands with their livestock and human managers do constitute complex adaptive systems. If this is so, then command-and-control approaches to rangeland policy and management are bound to fail.
Keywords: rangelands; complex adaptive system; resilience; institutions; agent-based models
Environmental processes have been modelled for decades. However, the need for integrated assessment and modeling (IAM) has grown as the extent and severity of environmental problems in the 21st Century worsens. The scale of IAM is not restricted to the global level as in climate change models, but includes local and regional models of environmental problems. This paper discusses various definitions of IAM and identifies five different types of integration that are needed for the effective solution of environmental problems. The future is then depicted in the form of two brief scenarios: one optimistic and one pessimistic. The current state of IAM is then briefly reviewed. The issues of complexity and validation in IAM are recognised as more complex than in traditional disciplinary approaches. Communication is identified as a central issue both internally among team members and externally with decision-makers, stakeholders and other scientists. Finally it is concluded that the process of integrated assessment and modelling is considered as important as the product for any particular project. By learning to work together and recognise the contribution of all team members and participants, it is believed that we will have a strong scientific and social basis to address the environmental problems of the 21st Century.
Keywords: Integrated assessment and modelling; Integration; Communication; Multi-disciplinary teams
We developed a stylized mathematical model to explore the effects of physical, ecological, and economic factors on the resilience of a managed fire-driven rangeland system. Depending on grazing pressure, the model exhibits one of three distinct configurations: a fire-dominated, grazing-dominated, or shrub-dominated rangeland system. Transaction costs and costs due to shrub invasion, via their effect on grazing decisions, strongly influence which stable configuration is occupied. This, in turn, determines the resilience of the rangeland system. These results are used to establish conditions under which management for profit is consistent with the maintenance of resilience. Keywords: resilience; rangelands; multiple states; complex systems.
We developed a stylized mathematical model to explore the effects of physical, ecological, and economic factors on the resilience of a managed fire-driven rangeland system. Depending on grazing pressure, the model exhibits one of three distinct configurations: a fire-dominated, grazing-dominated, or shrub-dominated rangeland system. Transaction costs and costs due to shrub invasion, via their effect on grazing decisions, strongly influence which stable configuration is occupied. This, in turn, determines the resilience of the rangeland system. These results are used to establish conditions under which management for profit is consistent with the maintenance of resilience.
Keywords: resilience; rangelands; multiple states; complex systems.
Markets can show different types of dynamics, from quiet markets dominated by one or few products, to markets with constant penetration of new and reintroduced products. This paper explores the dynamics of markets from a psychological perspective using a multi-agent simulation model. The behavioural rules of the artificial consumers, the consumats, are based on a conceptual meta-theory from psychology. The artificial consumers have to choose each period between similar products. Products remain in the market as long as they maintain a minimum level of market share, else they will be replaced by a new product. Assuming a population of consumats with different preferences, and social networks, the model simulates adoption of new products for alternative assumptions on behavioural rules. Furthermore, the consequences of changing preferences and the size of social networks are explored. Results show that the behavioural rules that dominate the artificial consumer’s decision making determine the resulting market dynamics, such as fashions, lock-in and unstable renewal. Results also show the importance of psychological variables like social networks, preferences and the need for identity to explain the dynamics of markets.
Keywords: Social networks; Changing preferences; Consumer behaviour; Lock-in
Research in the field of “industrial metabolism” traditionally has been focused on measuring and describing physical flows of economic systems. The “metabolism” of economic systems, however, changes over time, and measuring material flows is insufficient to understand this process. Understanding the relation between economic activities and material flows can help to unravel the socio-economic causes of these physical flows. Three issues are addressed: The importance of spatial scales and trade flows, empirical analysis of relations between economic development and material flows, and treatment of behaviour of and interactions between stakeholders. For each of these issues, methods for analysis are suggested.
Keywords: industrial metabolismmaterial flowsstructural decomposition
Truck tyres can cause significant environmental pressure through the life cycle. The main aim of this paper is investigate to what extent international policy measures on foreign trade, international recycling and harmonisation of legislation can contribute in effectively reducing environmental pressure caused in the truck tyre life cycle. A two-region simulation model, representing Western and Eastern Europe, is developed that integrates the complete life cycle, incorporates environmental impacts in its economic analysis, is technically dynamic by accounting for learning-by-doing effects, and allows for variations in trade of new and old truck tyres. In this study the economic, environmental and social effectiveness of harmonisation and trade measures in the European life cycle for truck tyre is tested. Several conclusions can be drawn from the model simulations. First, the environmental effects caused by the trade of used tyres from Western to Eastern Europe are of limited impact on the overall environmental damage caused by truck tyres. The consumption stage is by far the main contributor to environmental damage. Within the marginal analysis of trade, harmonisation of disposal fees illustrated to generate very limited positive results. The private and external costs in the solid waste management (SWM) stage are too limited to have a notable impact on the overall configuration of the European tyre life cycle. The introduction of strict laws on tread depth in Eastern Europe has a much stronger impact on material flows than the harmonisation scenario. This suggests that domestic policy measures should be the primarily focus on interventions in this stage of the life cycle, for instance, by improving the management of tyre pressure. Because trade of used tyres has little impact on the consumption stage, this issue should not get priority in European environmental programs.
Keywords: International trade; Recycling; Environmental policy; Tyres; Europe
Despite the abundance of empirical data on household energy consumption, it is hard to predict future developments because of the complexity of the household system. Multi-agent simulation offers a tool to get a better understanding of the relevant behavioural dynamics of the household system. This would allow for an early diagnosis and response to unwanted developments. A computer simulation of consumer behaviour has been developed on the basis of a meta-model of behaviour, which integrates various relevant behavioural theories. This so-called consumat approach has been applied to issues such as the lock-in of consumption patterns and the management of a common resource, and has been applied in an integrated ecological-economic model. This paper discusses the basic principles of the consumat approach, summarises some results, and draws conclusions with respect to the application of this approach in the domain of household consumption.
Keywords: behavioural dynamics; consumat; consumer behaviour; household consumption; modelling; multi-agent simulation.
A new perspective for studying the complex interactions between human activities and ecosystems is proposed. It is argued that biological immune systems share a number of similarities with ecological economic systems in terms of function. These similarities include the system’s ability to recognize harmful invasions, design measures to control and destroy these invasions, and remember successful response strategies. Studying both the similarities and the differences between immune systems and ecological economic systems can provide new insights on ecosystem management.
Keywords: adaptive systems, artificial immune systems, biological invasions, ecological economic systems, ecosystem management, immune systems, institutions, models.
Ecosystem management requires the explicit treatment of interactions between humans and ecosystems. An exploratory model for integrating social and ecological dynamics was introduced to study ecosystem management strategies. This paper focuses on the management of lake eutrophication. The model was developed to include the dynamics of the lake, the behaviour of agents using phosphorus for agricultural purposes, and the interactions between ecosystem and farmers. Analyses with the model showed that the dominating type of cognitive processing was a relevant factor in the response to uncertainty and policy measures. A higher target level for returns on the use of phosphorus was found to lead to a more intensive use of phosphorus and to higher levels of phosphorus in the lake. Simulated farmers used phosphorus more intensively in situations with high natural variability. A tax on phosphorus had little effect on the behaviour of the farmers when they felt uncertain and had low target levels for returns.
Keywords: Lake management; Social psychology; Resilience; Eutrophication; Multi-agent modelling; Integrated modeling.
A sequential optimization approach is applied to optimize the behavior of a complex dynamical system. It sequentially solves a large set of mathematical equations and next optimizes the behavior of a reduced-system, fixing certain variables of the larger original problem. These two steps are repeated till convergence occurs. The approach is applied to the problem of identifying response strategies for climate change caused by antropogenic emissions of different trace gases. The convergence properties are analyzed for this example.
Keywords: Sequential optimization; Sequential reduced-system programming; Dynamical system.
Die Lenkung der gegenwärtigen konsum- und produktionsmuster in eine nach- haltigere richtung erfordert eine ausführliche studie des menschlichen Verhal- tens. um dessen komplexität angemessen zu berücksichtigen, wird hier ein multi-agenten-ansatz vorgeschlagen, der erkenntnisse der sozialpsychologie integriert. am Beispiel des Übergangs von einer fischerei- zu einer Bergbauge- sellschaft wird gezeigt, wie sich unterschiedliche Verhaltensannahmen auf die mensch-umwelt-Beziehungen auswirken.
Markets can show different types of dynamics, ranging from stable markets dominated by one or a few products, to fluctuating markets where products are frequently being replaced by new versions. This paper explores the dynamics of markets from a psychological perspective using a multi-agent simulation model. The behavioural rules of the artificial consumers, the consumats, are based on a conceptual meta-theory from psychology. The artificial consumers have to choose each period between different products. Products remain on the market for as long as their market share exceeds a minimum level. If not, it will be replaced by a new product.
Simulation experiments are being performed with a population of consumats having different preferences. Results show that the dominating type of cognitive (choice) process has large consequences for the resulting market dynamics. Moreover, the size of the social network affects the market dynamics too.
Keywords: social networks; consumer behaviour; market dynamics.
By evaluating tires from a perspective of industrial metabolism, potential novel and practical ways to reduce their environmental impact can be found. This may be achieved by focusing on technological issues such as choosing materials, designing products, and recovering materials, or by looking at institutional and social barriers and incentives such as opening waste markets or changing consumer behavior. A model is presented for the life cycle of truck tires in Western Europe that is dynamic in nature and values both environmental and economic consequences. Various scenarios are simulated including longer tire lifetimes, better maintenance of tire pressure, increased use of less-expensive Asian tires, and increased use of fuel efficiency-enhancing tires (“eco-tires”). Tentative results indicate that, among other things, more than 95% of the overall environmental impact during the life of a tire occurs during the use of the tire, due to the impact of tires on automotive fuel efficiency. Better maintenance of tire pressure and use of eco-tires produce greater environmental and economics benefits than more-durable and/or less-expensive (Asian) tires. These results imply that the emphasis in environmental policies related to tires should shift from the production and the waste stages to the consumption stage. It also suggests that the focus on materials throughput and associated improvements through factor 4 or factor 10 advances in reduction in mass are less important than the quality of the tires and their management.
In mainstream economy, behaviour is often formalised following the rational actor-approach. However, in real life the behaviour of people is typified by multidimensional optimisation. To realise this, people engage in cognitive processes such as social comparison, imitation and repetitive behaviour (habits) so as to efficiently use their limited cognitive resources. A multi-agent simulation program is being developed to study how such micro-level processes affect macro-level outcomes. Sixteen agents are placed in a micro-world, consisting of a lake and a gold mine. Each agent’s task is to satisfy its personal needs by fishing and/or mining, whereby they find themselves in a commons dilemma facing the risk of resource depletion. Homo economicus and Homo psychologicus are formalised to study the effects of different cognitive processes on the agents’ behaviour. Results show that for the H. psychologicus the transition from a fishing to a mining society is more complete than for the H. economicus. Moreover, introducing diversity in agents’ abilities causes the H. economicus on the average to decrease its time spent working, whereas for the H. psychologicus we observe an increase in the time spent working. These results confirm that macro-level indicators of sustainability, such as pollution and fish-harvest, are strongly and predictably affected by behavioural processes at the micro-level. It is concluded that the incorporation of a micro-level perspective on human behaviour within integrated models of the environment yields a better understanding and eventual management of the processes involved in environmental degradation.
Keywords: Commons dilemma; Resource; Consumat; Simulation; Multi-agent; Dynamics; Psychology.
This paper describes an adaptive agent model of rangelands based on concepts of complex adaptive systems. The behavioural and biological processes of pastoralists, regulators, livestock, grass and shrubs are modelled as well as the interactions between these components. The evolution of the rangeland system is studied under different policy and institutional regimes that affect the behaviour and learning of pastoralists, and hence the state of the ecological system. Adaptive agent models show that effective learning and effective ecosystem management do not necessarily coincide and can suggest potentially useful alternatives to the design of policies and institutions.
Keywords: Complex adaptive systems; Ecosystem management; Rangelands; Adaptive agents.
This article describes a greenhouse gas (GHG) emissions scenario for a world that chooses collectively and effectively to pursue service-oriented economic prosperity while taking into account equity and environmental concerns, but without policies directed at mitigating climate change. After peaking around 2050 at 2.2 times the 1990 level of primary energy use, a number of factors lead to a primary energy use rate at the end of the next century that is only 40% higher than the 1990 rate. Among these factors are a stabilizing (and after 2050, declining) population, convergence in economic productivity, dematerialization and technology transfer, and high-tech innovations in energy use and supply. Land use-related emissions show a similar trend. Total CO2 emissions peak at 12.8 CtC/yr around 2040, after which they start falling off. Other GHG emissions show a similar trend. The resulting CO2-equivalent concentration continues to rise to about 600 ppmv in 2100. Present understanding of climate change impacts suggest that even in this world of high-tech innovations in resource use in combination with effective global governance and concern about equity and environment issues, climate policy is needed if mankind is to avoid dangerous interference with the climate system.
In this paper, we present results of simulationexperiments with the TIME-model on the issue ofmitigation strategies with regard to greenhouse gases.The TIME-model is an integrated system dynamics worldenergy model that takes into account the fact that the systemhas an inbuilt inertia and endogenouslearning-by-doing dynamics, besides the more commonelements of price-induced demand response and fuelsubstitution. First, we present four scenarios tohighlight the importance of assumptions on innovationsin energy technology in assessing the extent to whichCO2 emissions have to be reduced. The inertia ofthe energy system seems to make a rise ofCO2 emissions in the short term almostunavoidable. It is concluded that for the populationand economic growth assumptions of the IPCC IS92ascenario, only a combination of supply- anddemand-side oriented technological innovations incombination with policy measures can bring the targetof CO2-concentration stabilization at 550 ppmv bythe year 2100 within reach. This will probably beassociated with a temporary increase in the overallenergy expenditures in the world economy. Postponingthe policy measures will be more disadvantageous,and less innovation in energy technology will happen.
Addressing global change demands an integrative consideration of interactions between humans and the environment on a world wide scale. An assimilative integrated system approach seems to be appropriate for investigation of this complex global problem. In this paper an integrated modeling approach is proposed that is based on an evolutionary view on global change. A case study is worked out where images of the future using a multi-agent model are assessed, and where agents differ in their world view and thus also in their preferred management style. The perspective of agents may change due to new information they derive from the system. A simple model is constructed to illustrate the consequences of this approach on climate change scenarios.
Human activities change the environment on a global level. Global modelling is used to derive insights in the interactions between humans and their environment. However, the possibility to validate those global models is limited. In fact, too little information is available, many subjective assumptions are made and a single model cannot cover all relevant scale levels and processes. These limitations already appeared in the early seventies. Current global modelling activities still deal with the same dilemma’s, often in the same way as the strongly criticised world models of the early seventies. We sketch some recent developments which can help to manage the persistent dilemma’s. We focus on the use of different modelling paradigms and on the use of different world views to analyse the consequences of subjective assumptions to be made in global models.
Keywords: global modelling, validation, complexity, uncertainty.
We demonstrate an approach for integrating social and ecological models to study ecosystem management strategies. We focus on the management of lake eutrophication. A model has been developed in which the dynamics of the lake, the learning dynamics of society, and the interactions between ecology and society are included. Analyses with the model show that active learning is important to retain the resilience of lakes. Although very low levels of phosphorus in the water will not be reached, active learning reduce the chance of catastrophic high phosphorus levels.
Keywords: active learning, eutrophication, integrated modeling, lake dynamics, lake management, multi-agent modeling, phosphorus, resilience, restoration, simulation.
Many uncertainties and controversies surround the future of the global energy system. The Targets Image Energy (TIME) model of which a concise description is given, is used to explore the consequences of divergent assumptions about some uncertain and controversial issues. The IPCC-IS92a Conventional Wisdom scenario is used as a reference and, in combination with two other scenarios, discussed in the context of other recently published global energy scenarios.
Keywords: Global energy scenarios; Energy modelling; Climate change.
Lock-in denotes a phenomenon of monopolistic dominating technologies or consumer goods in a certain market. These lock-ins cannot be explained by superior characteristics of the good or technology. Previous studies mainly used probabilistic models to study lock-in effects. In this paper an integrated conceptual model of consumer behaviour is used to identify relevant processes of lock-in dynamics of consumption patterns. An agent-based model is developed to simulate consumats, artificial consumers, who are confronted with two similar products. We found two types of lock-in, namely, a spatial lock-in and a global level lock-in. The spatial lock-in related to the spatial patterns that occur in consumption patterns and relates to the satisfaction of the need for identity. The global lock-in relates to price effects and occurs only if individual preferences are not significantly weighted in the cognitive processing.
Keywords: Lock-in, multi-agent modelling, social psychology, need satisfaction, consumer behavior.
Global modeling has been used for decades to assess the possible futures of humanity and the global environment. However, these models do not always satisfactorily include the adaptive characteristics of systems. In this article, a general approach is used to simulate change and transition at a macrolevel due to adaptation at a microlevel. Tools from complex adaptive systems research are used to simulate the microlevel and consequently determine parameter values of the equation-based macrolevel model. Two case studies that applied this approach are reviewed. The first study assessed the efficacy of efforts to control malaria, whereas the second study used an integrated model to construct climate change scenarios by using various possible views on the nature of the climate system.
Key words: complex adaptive systems; global change; climate change; malaria; multiagent modeling; adaptation; coevolution; genetic algorithms.
To evaluate possible futures with regard to economy, energy and climate, a multi-agent modelling approach is used. Agents hold different perspectives on how the world functions (worldview) and how it should be managed (management style) and this is implemented in a simple dynamic model of the economy-energy-climate system. Each perspective is supported by a proportion of the agents, but this proportion changes in response to observations about the real world. In this way the totality of agents learn from their observations. It is concluded that this approach is a good illustration of how adaptive behavior can be included in global change modelling. Some exploratory experiments are done to address the consequences of surprises.
Keywords: Global change; Integrated assessment modeling; Perspectives; Multi-agent modeling.
The safe landing analysis has been devel oped to link short-term greenhouse gas emission targets to longer-term climate protection goals. The analysis was applied to the climate policy goals proposed by the European Union. This application and several presentations of the analysis during the negotiations on the Kyoto Protocol led to critical but constructive discussions. In this paper we discuss some of the key questions such as policy relevance, scientific credibility, use and adequacy of global indicators todetermine impact levels, technological feasibility and economic aspects. The results from the safe landing analysis were generally accepted by the policy community because it bridges the gap between policy needs and the understanding derived from complex but scientifically rigorous integrated assessment models.The selected indicators of the safe landing analysis are evaluated. It is shown that the indicators describing rates of change are as important for defining impacts and response policies as those describing only cumulative or absolute change. Lower levels of climatic change generally coincide with lower impact levels. However, only the lowest rates and levels of climate change allow natural ecosystems to adapt. It is further shown that the level of additional energy expenditures needed to meet such low impact levels strongly depends on the assumed technological development rates.
Workers at the Dutch National Institute of Public Health and the Environment (RIVM) have recently developed a new comput er tool called the Interactive Scenario Scanner (ISS). The tool enables users to interactively construct global greenhouse gas emission scenarios and evaluate their likely climate change impacts. In this way, the tool can be used to support a dialogue between scientists and policy makers on scenario development and help in selecting scenarios to be analysed with more sophisticated modelling tools, like RIVM’s IMAGE 2 model.
When tackling a subject as complex as global change and sustainable development, it is essential to be able to frame the issuesThis was one of the main reasons for developing the TARGETS model, an integrated model of the global system, consisting of metamodels of important subsystems. In this chapter we introduce TARGETS. Building on the previous chapters, we elaborate on the possibilities and limitations of integrated assessment models. Some of the key issues discussed are aggregation, model calibration and validation, and dealing with uncertainty.
This submodel simulates the supply and demand for fuels• and electricity, given a certain level of economic activity. It is linked to other submodels, for example through investment flows, population sizes and emissions. The energy model consists of five modules: Energy Demand, Electric Power Generation, and Solid, Liquid and Gaseous Fuel supply. Effects such as those of depletion, conservation, fuel substitution, technological innovation, and energy efficiency are incorporated in an integrated way, with prices as important signals. Renewable sources are included as a non-thermal electricity option and as commercial biofuels.
In this chapter we present simulation experiments and outcomes of the energy submodel TIME. First, the major controversies and uncertainties are discussed. Next, the cultural perspectives are introduced with reference to world energy, after which we clarify the way in which these are linked to assumptions and model routes. Some results of sensitivity and uncertainty analyses are also given. We discuss a few energy dystopias which could emerge if, for a given population-economy scenario, the world view and the management style within the energy system are discordant. Some conclusions are presented about the plausibility of and risks related to the Utopian energy futures. The impacts of the emissions from fossil fuel combustion on water, land, and element cycles are discussed in the next three chapters.
The influence of human activities on the environment has reached such a scale and complexity that unequivocal solutions to the dis ruption can no longer be given. That is why increasing use is being made of integrated assessment, which is a multi-discipli nary process, having as its objective the integration of scientific knowledge drawn from a variety of areas. One instrument that is used in this process is the computer simulation model. There are various types of these integrated assessment models (IAM), as they are called. In general, these models are a combination of simplified versions of different expert models, allowing future scenarios to be analyzed of the entire problem area.
As the resistance of the malaria parasite to antimalarial drugs continues to increase, as does that of the malarial mosquito to insecticides, the efficacy of efforts to control malaria in many tropical countries is diminishing. This trend, together with the projected consequences of climate change, may prove to exacerbate substantially the significance of malaria in the coming decades.
In this article we introduce the use of an evolutionary modeling approach to simulate the adaptation of mosquitoes and parasites to the available pesticides and drugs. By coupling genetic algorithms with a dynamic malaria-epidemiological model, we derive a complex adaptive system capable of simulating adapting and evolving processes within both the mosquito and the parasite populations.
This approach is used to analyze malaria management strategies appropriate to regions of higher and lower degrees of endemicity. The results suggest that adequate use of insecticides and drugs may reduce the occurrence of malaria in regions of low endemicity, although increased efforts would be necessary in the event of a climate change. However, our model indicates that in regions of high endemicity the use of insecticides and drugs may lead to an increase in incidence due to enhanced resistance development. Projected climate change, on the other hand, may lead to a limited reduction of the occurrence of malaria due to the presence of a higher percentage of immune persons in the older age class.
We regard the global climate system as a controlled dynamic system, with controls corresponding to economic activities causing emissions of greenhouse gases. Previous optimization studies for climate change have used descriptions of the environmental system which are found to be too unrepresentative of what is known in the scientific community. In this paper an approach is applied which tries to include a more sophisticated model of the environmental system. The resulting continuous dynamic control problem is solved by the application of a set of non-linear optimization techniques to find optimal response strategies to maximize the discounted sum of future consumption while adhering to certain environmental constraints.
Keywords: Non-linear optimization; CO2; Climate change.
The objective of this paper is to demonstrate a methodology whereby reductions of greenhouse gas emissions can be allocated on a regional level with minimal deviation from the “business as usual emission scenario”. The methodology developed employs a two stage optimization process utilizing techniques of mathematical programming. The stage one process solves a world emission reduction problem producing an optimal emission reduction strategy for the world by maximizing an economic utility function. Stage two addresses a regional emission reduction allocation problem via the solution of an auxiliary optimization problem minimizing disruption from the above business as usual emission strategies. Our analysis demonstrates that optimal CO2 emission reduction strategies are very sensitive to the targets placed on CO2 concentrations, in every region of the world. It is hoped that the optimization analysis will help decision-makers narrow their debate to realistic environmental targets.
The development of climate change response strategies is expected to remain an important issue in the next few decades. The use of optimization techniques might serve as a helpful guide in this process. Although, in recent years, a number of studies have focused on optimization techniques, the optimization models do not fully employ the dynamics of climatic and economic systems. In this paper a heuristic is introduced that combines an integrated simulation model and an optimization technique (local search). This approach may be considered as a first step towards a more comprehensive and systematic analysis of climate change response strategies in a dynamic setting described by a simulation model. Results of a number of experiments in which the heuristic is applied to the integrated global assessment model TARGETS are discussed.
Cultural perspectives play an important role in framing international climate policy. The concept we have introduced is designed to enable quantification of the influence of such cultural perspectives on the allocation of fossil CO2 emission rights. A model is presented which allocates future emission rights to world regions. An emission budget which incorporates an historical component is defined for the specific period which is required if climate change policy targets are to be met. Allocation of the budget to regions is based on a weighted mix of indicators such as population size, GNP and energy consumption. Subtracting historical emissions results in future regional emission rights. Uncertainties in the selection of parameter values for the model and in generating scenarios of future developments are here regarded as being related to cultural perspectives. We have assumed that cultural perspectives can be quantified by reference to distributions of preferred parameter values and preferred future scenarios. Distributions of regional emission rights biased towards preferred allocations as determined by the perspectives can thus be described. In fact, the proposed approach envisages an uncertainty analysis based on the characteristics of cultural perspectives.
Keywords: Climate change; CO2; Cultural perspectives; Allocation of emission rights.
The feasibility of an effective international response to anticipated climate change is dependent on the recognition of the present and historical inequities between developing and industrialized countries. Developing countries should be enabled and supported to continue their development towards higher standards of living in a fashion that is consistent with the sustainability of the global biosphere. This paper evaluates long-term climate strategies by which the burden of mitigating climate change by controlling CO2 emissions is shared equitably. Here we use as a possible criterion of equity, that every human being, past or future, is allowed to emit the same carbon quotum on an annual basis, which, as a theoretical concept, could provide for intergenerational and international equity throughout the world. In order to do this we first define the global carbon budget as the cumulated CO2 emissions over the period 1800 till 2100, from 1990 described by an emission scenario. This budget determines the permitted CO2 emissions per capita using past and future population estimates. Next, we introduce the concept of ’emission debt’, defined by the difference between the cumulated allowed CO2 emissions, based on the permitted emission quota per capita, and the actual historical CO2 emissions. Finally the remaining carbon budget, described as the global carbon budget (1800-2100) minus the actual cumulated CO2 emissions (1800-1990) is allocated to the different world regions, taking into account the regional past CO2 emissions. This gives the future emission quota per capita. The results show that past industrialisation has coincided with a large relative contribution of the rich regions to the rise in CO2 concentration, an estimated 40 per cent for the European Community and North America, which have built up an emission debt of 36 GtC and 75 GtC, respectively, using recent World Bank projections of population growth. The developing countries, however, have built up an emission credit of 24 GtC. These regional emisson debts and credits increase the future per capita budget for the developing regions till 0.2-0.8 ton C/cap yearly, whereas North America and the EC end up with a negative future carbon budget of 0.4 to 1.5 ton C/cap yearly. Even if the IPCC Business-as-Usual scenario is considered as reference, the future emission quota of most industrialized countries are lower than their present per capita emissions, i.e, North America has a negative future carbon budget of 0.3 tC/cap yearly.
Keywords: future emissions allocation; carbon dioxide; CO2; carbon emissions; emission debt; global carbon budget; global warming; Integrated Model to Assess the Greenhouse Effect; IMAGE; sustainable climate strategies; sustainable temperature targets; sustainability; sustainable development.