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