scholarly journals Rangelands, pastoralists and governments: interlinked systems of people and nature

2002 ◽  
Vol 357 (1421) ◽  
pp. 719-725 ◽  
Author(s):  
Brian H. Walker ◽  
Marco A. Janssen

We analyse commercially operated rangelands as coupled systems of people and nature. The biophysical components include: (i) the reduction and recovery of potential primary production, reflected as changes in grass production per unit of rainfall; (ii) changes in woody plants dependent on the grazing and fire regimes; and (iii) livestock and wool dynamics influenced by season, condition of the rangeland and numbers of wild and feral animals. The social components include the managers, who vary with regard to a range of cognitive abilities and lifestyle choices, and the regulators who vary in regard to policy goals. We compare agent–based and optimization models of a rangeland system. The agent–based model leads to recognition that policies select for certain management practices by creating a template that governs the trajectories of the behaviour of individuals, learning, and overall system dynamics. Conservative regulations reduce short–term loss in production but also restrict learning. A free–market environment leads to severe degradation but the surviving pastoralists perform well under subsequent variable conditions. The challenge for policy makers is to balance the needs for learning and for preventing excessive degradation. A genetic algorithm model optimizing for net discounted income and based on a population of management solutions (stocking rate, how much to suppress fire, etc.) indicates that robust solutions lead to a loss of about 40% compared with solutions where the sequence of rainfall was known in advance: this is a similar figure to that obtained from the agent–based model. We conclude that, on the basis of Levin's three criteria, rangelands with their livestock and human managers do constitute complex adaptive systems. If this is so, then command–and–control approaches to rangeland policy and management are bound to fail.

Author(s):  
Professor Michael E. Wolf-Branigin ◽  
Dr William G. Kennedy ◽  
Dr Emily S. Ihara ◽  
Dr Catherine J. Tompkins

2017 ◽  
Vol 46 (3) ◽  
pp. 469-489
Author(s):  
Cheng Guo ◽  
Carsten M Buchmann ◽  
Nina Schwarz

Urban sprawl and income segregation are two undesired urban patterns that occur during urban development. Empirical studies show that income level and inequality are positively correlated with urban sprawl and income segregation, respectively. However, the relationship between urban sprawl and income segregation is not only rarely investigated but also shows ambiguous empirical results when it is. Therefore, in this study, we built a stylized agent-based model with individual behaviours based on Alonso’s bid rent theory and ran simulations with different combinations of income level and income inequality. We measured the overall emergent patterns with indicators for urban sprawl and income segregation. The model confirms the established positive correlations between income level and urban sprawl and between income inequality and segregation. Furthermore, the model shows a negative correlation between urban sprawl and income segregation under free market conditions. The model indicates that without any policy implementation, a city will either suffer from urban sprawl or income segregation. Thus, this study serves as a starting point to study the effects of different urban planning policies on these two urban problems.


Agent based modeling is one of many tools, from the complexity sciences, available to investigate complex policy problems. Complexity science investigates the non-linear behavior of complex adaptive systems. Complex adaptive systems can be found across a broad spectrum of the natural and human created world. Examples of complex adaptive systems include various ecosystems, economic markets, immune response, and most importantly for this research, human social organization and competition / cooperation. The common thread among these types of systems is that they do not behave in a mechanistic way which has led to problems in utilizing traditional methods for studying them. Complex adaptive systems do not follow the Newtonian paradigm of systems that behave like a clock works whereby understanding the workings of each of the parts provides an understanding of the whole. By understanding the workings of the parts and a few external rules, predictions can be made about the behavior of the system as a whole under varying circumstances. Such systems are labeled deterministic (Zimmerman, Lindberg, & Plsek, 1998).


2006 ◽  
Vol 21 (4) ◽  
pp. 272-283 ◽  
Author(s):  
Enrique Canessa ◽  
Rick L. Riolo

Organizations that make use of computer information systems (CIS) are prototypical complex adaptive systems (CAS). This paper shows how an approach from Complexity Science, exploratory agent-based modeling (ABM), can be used to study the impact of two different modes of use of computer-mediated communication (CMC) on organizational culture (OC) and performance. The ABM includes stylized representations of (a) agents communicating with other agents to complete tasks; (b) an OC consisting of the distribution of agent traits, changing as agents communicate; (c) the effect of OC on communication effectiveness (CE), and (d) the effect of CE on task completion times, that is, performance. If CMC is used in a broad mode, that is, to contact and collaborate with many, new agents, the development of a strong OC is slowed, leading to decreased CE and poorer performance early on. If CMC is used in a local mode, repeatedly contacting the same agents, a strong OC develops rapidly, leading to increased CE and high performance early on. However, if CMC is used in a broad mode over longer time periods, a strong OC can develop over a wider set of agents, leading to an OC that is stronger than an OC which develops with local CMC use. Thus broad use of CMC results in overall CE and performance that is higher than is generated by local use of CMC. We also discuss how the dynamics generated by an ABM can lead to a deeper understanding of the behavior of a CAS, for example, allowing us to better design empirical longitudinal studies.


2014 ◽  
Vol 7 (2) ◽  
pp. 137
Author(s):  
Alexandra Esperança Da Cunha Pimentel de Meira ◽  
Victor Meyer Jr., ◽  
Lucilaine Pascuci

The aim of this study is to analyze the strategic practices developed by a Brazilian nonprofit organization, which focuses on the promotion of social entrepreneurship at the bottom of the pyramid. The major goal of the study is to focus on the strategies of its project managers. The study is based on the concepts of Salamon (2003) and Moore (2000) and the role played by the nonprofit organization in the same manner that entrenches the theories of complex adaptive systems and the loosely coupled systems. It has also highlighted the use of strategy-as-practice as a theoretical basis to better understand the social actions. It is a case study of a qualitative nature. Data were collected from analysis of documents, non-participant observation and interviews. Data analysis revealed that project managers played a critical role as strategists. In their social practices they combine experience, sensemaking, interactions, decision making and knowledge together with neutrality and autonomy for action. The results revealed that the number of micro-entrepreneurs who benefited from the projects has grown significantly during the period of the study. Likewise, the income of these micro-entrepreneurs and that of their families has displayed a steady increase. The conclusion indicates that strategic practices carried out by project managers have brought social value to micro-entrepreneurs and contributed significantly to the achievement of the organization`s goals.


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