Marco A. Janssen

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