Fig 6 - uploaded by Graeme S. Cumming
Content may be subject to copyright.
3 Spatial depiction of an implementation of the prisoner's dilemma game in NetLogo (Wilensky, 1999, 2002). Each pixel in this 150 × 150-pixel world represents an actor who can interact with his/her eight neighbours in each iteration of the model. Actors cooperate (blue) or defect (red) with equal probability at the start of the model. From then on, if an actor has cooperated, its score will be the number of its neighbors that also cooperated; if it defects, its score will be the product of the defection-award ratio and the number of cooperating neighbors (i.e. the actor has taken advantage of the patches that cooperated). For the next iteration of the model, each actor will adopt the strategy of its highest-scoring neighbor from the previous round. In this figure, blue shading means that the actor cooperated in the previous and current round; red, that it defected in the previous iteration as well as the current round; green, that it cooperated in the previous round but defected in the current round; and yellow, that it defected in the previous round but cooperated in the current round. This particular simulation used a defection-award ratio of 1.58, which results in a dynamic pattern with similar proportions of defectors and cooperators. Netlogo can be downloaded or run on-line at http://ccl.northwestern.edu/netlogo/4.1.1/ 

3 Spatial depiction of an implementation of the prisoner's dilemma game in NetLogo (Wilensky, 1999, 2002). Each pixel in this 150 × 150-pixel world represents an actor who can interact with his/her eight neighbours in each iteration of the model. Actors cooperate (blue) or defect (red) with equal probability at the start of the model. From then on, if an actor has cooperated, its score will be the number of its neighbors that also cooperated; if it defects, its score will be the product of the defection-award ratio and the number of cooperating neighbors (i.e. the actor has taken advantage of the patches that cooperated). For the next iteration of the model, each actor will adopt the strategy of its highest-scoring neighbor from the previous round. In this figure, blue shading means that the actor cooperated in the previous and current round; red, that it defected in the previous iteration as well as the current round; green, that it cooperated in the previous round but defected in the current round; and yellow, that it defected in the previous round but cooperated in the current round. This particular simulation used a defection-award ratio of 1.58, which results in a dynamic pattern with similar proportions of defectors and cooperators. Netlogo can be downloaded or run on-line at http://ccl.northwestern.edu/netlogo/4.1.1/ 

Source publication
Chapter
Full-text available
In recent times, and particularly since the advent of the internet, graph theory (and its sub-discipline of network analysis) has taken on a new importance as one of the branches of mathematics that is best suited to exploring questions of connectivity and relationality. Just about anything that involves exchanges between manageable numbers of dist...

Similar publications

Article
Full-text available
Abstract Understanding the complex interlinkages between humans and nature is crucial for developing strategies to effectively manage natural resources and to enhance resilience of social–ecological systems (SES). Network analysis bears great potential to advance such comprehension of SESs because it allows for identifying and analysing direct and...
Poster
Full-text available
Biodiversity is integral part of complex social-ecological systems, at the interface of natural, social, economic, and law sciences. Emerging theories and new multi-disciplinary approaches point to the importance of protecting functional biodiversity to assess and actively manage social-ecological system (SES) resilience. Marine Protected Areas (MP...

Citations

... Dependence on the country's agricultural policies or international fluctuation of prices 355 negatively affect resilience (2,83). Therefore, it is necessary to include power relations derived 356 from global scales, which prevent peasants from reaching full autonomy in decision making or 357 real participation in processes of political definition (8,16,19,84). ...
Preprint
Full-text available
This article proposes a conceptual and methodological framework for analyzing agroecosystem resilience, which incorporates agrarian structure and peasant community agency. The methodology is applied to a comparison of two peasant communities in Latin America (Brazil and Colombia), emphasizing the capacity to transform unsustainable power structures in place of adapting to them. This application demonstrates that when agency is strongly developed, as in the case of Brazil, it is possible to transform structural conditions that restrict resilience. The inclusion and consideration of biophysical variables, management practices, agrarian structure and agency, through a participatory approach, allows for the identification of factors that inhibit or potentiate the resilience of agroecosystems.
Article
Full-text available
This article proposes a conceptual and methodological framework for analyzing agroecosystem resilience, in which aspects such as agrarian structure and peasant community agency are included as determining factors. The methodology is applied to a comparison of two peasant communities in Latin America (Brazil and Colombia), emphasizing the capacity to transform unsustainable power structures in place of adapting to them. We find that when agrarian structure is more equitable and peasant agency is strongly developed through political formation, organization and women’s participation, then there is a greater construction of resilience that improves peasant livelihoods and dignity. This application demonstrates that when agency is strongly developed, as in the case of Brazil, it is possible to transform structural conditions that restrict resilience. The inclusion and consideration of biophysical variables, management practices, agrarian structure and agency, through a participatory approach, allows for the identification of factors that inhibit or potentiate the resilience of agroecosystems.
Article
Full-text available
Transportation networks daily provide accessibility and crucial services to societies. However, they must also maintain an acceptable level of service to critical infrastructures in the case of disruptions, especially during natural disasters. We have developed a method for assessing the resilience of transportation network topology when exposed to environmental hazards. This approach integrates graph theory with stress testing methodology and involves five basic steps: (1) establishment of a scenario set that covers a range of seismic damage potential in the network, (2) assessment of resilience using various graph-based metrics, (3) topology-based simulations, (4) evaluation of changes in graph-based metrics, and (5) examination of resilience in terms of spatial distribution of critical nodes and the entire network topology. Our case study was from the city of Kathmandu in Nepal, where the earthquake on April 25, 2015, followed by a major aftershock on May 12, 2015, led to numerous casualties and caused significant damage. Therefore, it is a good example for demonstrating and validating the developed methodology. The results presented here indicate that the proposed approach is quite efficient and accurate in assisting stakeholders when evaluating the resilience of transportation networks based on their topology.
Article
As human activities increasingly threaten the ecosystems on which they depend, one of the main questions our societies are facing is related to the resilience – seen as a necessary element of sustainability – of social–ecological systems (SESs). SESs are composed of many heterogeneous elements including human actors such as institutions and resource users, and natural components such as land patches, animal species, etc. The numerous relationships between these different entities shape complex, dynamic networks of social–ecological interdependencies. Once described as networks, SESs can be analysed using a variety of network metrics, which may potentially help to better quantify and evaluate the resilience of SESs to external or internal perturbations. In this paper, we provide a broad overview of the latest progress in network theory as applied to SESs and discuss how network metrics may be used to assess the sustainability of an SES.