Abstract
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.
Abstract
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.
Abstract
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
Abstract
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.
Abstract
Within the field of innovation diffusion, many empirical studies have been conducted on the factors that influence the propagation of new ideas and products. From the natural sciences, percolation theory has been used as a starting point to explore the dynamics of innovation diffusion, in particular the occurrence of hits and flops (Solomon et al., 2000). Whereas the latter model is based on a regular network connecting individual consumers and assumes that consumers have only individual preferences, innovation diffusion theory, as well as empirical data, suggests that consumers differ concerning the number of contacts they have and the degree to which social preferences determine their choice to adopt. To test the impacts of these assumptions on the simulated diffusion dynamics, we replicated the Solomon et al. (2000) model and experimented with scale-free networks and social preferences. Results indicate that network shape and social preferences have large impacts on the chances that an innovation either becomes a hit or a flop. To increase the empirical validity of simulated diffusion dynamics we suggest assessing the network structure between consumers as well as the social relevance of the markets.
Keywords: Innovation diffusion, percolation, social networks, preferences.
