We examined the principal effects of different information network topologies for local adaptive management of natural resources.
We used computerized agents with adaptive decision algorithms with the following three fundamental constraints: (1) Complete
understanding of the processes maintaining the natural resource can never be achieved, (2) agents can only learn by experimentation
and information sharing, and (3) memory is limited. The agents were given the task to manage a system that had two states:
one that provided high utility returns (desired) and one that provided low returns (undesired). In addition, the threshold
between the states was close to the optimal return of the desired state. We found that networks of low to moderate link densities
significantly increased the resilience of the utility returns. Networks of high link densities contributed to highly synchronized
behavior among the agents, which caused occasional large-scale ecological crises between periods of stable and high utility
returns. A constructed network involving a small set of experimenting agents was capable of combining high utility returns
with high resilience, conforming to theories underlying the concept of adaptive comanagement. We conclude that (1) the ability
to manage for resilience (i.e., to stay clear of the threshold leading to the undesired state as well as the ability to re-enter
the desired state following a collapse) resides in the network structure and (2) in a coupled social–ecological system, the
systemwide state transition occurs not because the ecological system flips into the undesired state, but because managers
lose their capacity to reorganize back to the desired state.
An erratum to this article can be found at . 相似文献
Objective: The Multidimensional Driving Style Inventory (MDSI) has been widely used in assessing the associations between driving styles and traffic violations and accidents in different cultural contexts. Due to the lack of a valid instrument to assess driving style, studies concerning driving style and its influence factors are limited in China. Thus, this study aimed to adapt and validate a Chinese version of the MDSI.
Methods: Seven hundred and sixty drivers aged from 19 to 60 years old were asked to complete the MDSI and a personality scale (trait anger, sensation seeking, altruism, and normlessness). Exploratory factory analysis (EFA) and confirmatory factor analysis (CFA) were used to obtain the factorial structure of the MDSI. The external validity of the MDSI was then evaluated by examining the associations between driving styles and personality traits, demographic variables, and traffic violations and crashes.
Results: EFA revealed a 6-factor structure of the MDSI (i.e., risky, anxious, angry, distress reduction, careful, and dissociative driving styles). CFA confirmed that the model fit of the MDSI was acceptable. The MDSI factors were moderately or weakly correlated with trait anger, sensation seeking, altruism, and normlessness. Significant gender and age differences in driving styles were found. Moreover, drivers who had traffic violations or crashes in the past year scored higher on risky and angry driving styles and lower on careful driving style than those who had not have traffic violations or crashes.
Conclusions: The Chinese version of the MDSI proved to be a reliable, valid, and highly useful instrument. It could be used to assess Chinese drivers who are at risk due to their maladaptive driving styles. 相似文献
Reverse logistics (RL) has been applied in many industries and sectors since its conception. Unlike forward logistics, retracing consumer goods from the point of consumption to the point of inception is not a well-studied process. It involves many uncertainties such as time, quality and quantity of returns. The returned products can be remanufactured, have parts harvested, or be disposed safely. It is important to implement these activities in a cost-effective manner. The aim of this research is to measure the performance of the RL enterprise with the help of an agent-based simulation model. The major entities in the RL network are considered as Agents that can act independently. There are several different agents: collector agent, sorting-cum-reuse agent, remanufacturing agent, recycler agent, supplier agent and distributor agent. The individual performances of the agents are measured and recommendations are given to improve their performance, leading to the enhancement of the total performance of the RL enterprise. The approach is applied to a case study involving cell phone remanufacturing. 相似文献
Mitigation of eutrophication, intensified by excessive nutrient load discharge in wastewaters regulated by restrictive legal requirements, remains one of today’s most important global problems. Despite implementation of the Water Framework Directive, the Urban Wastewater Directive and the HELCOM recommendations, the actual condition of surface water is still not satisfactory. In response to the above, the study presents an alternative approach for surface water protection against eutrophication based on the selection of appropriate nutrient removal technologies. An activated sludge model simulation was used to enable the identification of environmentally justified nutrient removal systems with lowest eutrophication potential of treated wastewater conditioned by bioavailable nutrient forms content. Based on the outcome of the study, the 3-stage Bardenpho system was identified as the most efficient for bioavailable phosphorus removal, while the Johannesburg system proved to have the highest efficiency for bioavailable nitrogen removal. The proposed eutrophication mitigation approach underlines the need for a reconsideration of current legal regulations which ignore nutrient bioavailability and key eutrophication limiting factors. 相似文献