EMERGENT FEATURES IN A GENERAL FOOD WEB SIMULATION: LOTKA–VOLTERRA, GAUSE'S LAW, AND THE PARADOX OF ENRICHMENT

2013 ◽  
Vol 16 (08) ◽  
pp. 1350014 ◽  
Author(s):  
TED CARMICHAEL ◽  
MIRSAD HADZIKADIC
Keyword(s):  
Simulation Model ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Marine Ecosystem ◽  
System Level ◽  
Computer Simulation Model ◽  
Agent Based ◽  
Predator Prey ◽  
Paradox Of Enrichment ◽  
Complex Adaptive

Computer simulations of complex food-webs are important tools for deepening our understanding of these systems. Yet most computer models assume, rather than generate, key system-level patterns, or use mathematical modeling approaches that make it difficult to fully account for nonlinear dynamics. In this paper, we present a computer simulation model that addresses these concerns by focusing on assumptions of agent attributes rather than agent outcomes. Our model utilizes the techniques of complex adaptive systems and agent-based modeling so that system level patterns of a marine ecosystem emerge from the interactions of thousands of individual computer agents. This methodology is validated by using this general simulation model to replicate fundamental properties of a marine ecosystem, including: (i) the predator–prey oscillations found in Lotka–Volterra; (ii) the stepped pattern of biomass accrual from resource enrichment; (iii) the Paradox of Enrichment; and (iv) Gause's Law.

Simulation model of supply networks development

2019 ◽  
Author(s):  
Petr Fiala ◽  
Martina Kuncová
Keyword(s):  
Simulation Model ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Initial Conditions ◽  
Fitness Function ◽  
Network Systems ◽  
Network Growth ◽  
Fitness Value ◽  
Complex Adaptive ◽  
Fixed Structure

The paper is dedicated to network development in the network economy. The current economy needs to look not only at networks with only dynamic flows and with a fixed structure, but as a dynamic system its structure evolves and changes. Structure and behaviour dynamics of network systems can be modelled as complex adaptive systems and use agent-oriented simulation to demonstrate origin, perturbation effects, and sensitivity with regard to initial conditions. Survival of firms is associated with the value of so-called fitness function. Firms whose fitness value falls below a certain threshold will be extinguished. In this way, it is possible to partially model network growth. A simulation model in SIMUL8 is proposed.

Applying complex adaptive systems to agent-based models for social programme evaluation

2018 ◽  
pp. 312-326 ◽  
Author(s):  
Professor Michael E. Wolf-Branigin ◽  
Dr William G. Kennedy ◽  
Dr Emily S. Ihara ◽  
Dr Catherine J. Tompkins
Keyword(s):  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Programme Evaluation ◽  
Agent Based Models ◽  
Agent Based ◽  
Complex Adaptive ◽  
Social Programme

scholarly journals Performance management in complex adaptive systems: a conceptual framework for health systems

2021 ◽  
Vol 6 (7) ◽  
pp. e005582
Author(s):  
Tom Newton-Lewis ◽  
Wolfgang Munar ◽  
Tata Chanturidze
Keyword(s):  
Performance Management ◽  
Health Systems ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Collective Responsibility ◽  
System Level ◽  
Empirical Literature ◽  
Current Evidence ◽  
Current Evidence Base ◽  
Complex Adaptive

Existing performance management approaches in health systems in low-income and middle-income countries are generally ineffective at driving organisational-level and population-level outcomes. They are largely directive: they try to control behaviour using targets, performance monitoring, incentives and answerability to hierarchies. In contrast, enabling approaches aim to leverage intrinsic motivation, foster collective responsibility, and empower teams to self-organise and use data for shared sensemaking and decision-making.The current evidence base is too limited to guide reforms to strengthen performance management in a particular context. Further, existing conceptual frameworks are undertheorised and do not consider the complexity of dynamic, multilevel health systems. As a result, they are not able to guide reforms, particularly on the contextually appropriate balance between directive and enabling approaches. This paper presents a framework that attempts to situate performance management within complex adaptive systems. Building on theoretical and empirical literature across disciplines, it identifies interdependencies between organisational performance management, organisational culture and software, system-level performance management, and the system-derived enabling environment. It uses these interdependencies to identify when more directive or enabling approaches may be more appropriate. The framework is intended to help those working to strengthen performance management to achieve greater effectiveness in organisational and system performance. The paper provides insights from the literature and examples of pitfalls and successes to aid this thinking. The complexity of the framework and the interdependencies it describes reinforce that there is no one-size-fits-all blueprint for performance management, and interventions must be carefully calibrated to the health system context.

Agent-Based Modeling

2017 ◽  
pp. 36-51
Keyword(s):  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Complexity Science ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Linear Behavior ◽  
Complex Adaptive ◽  
Economic Markets ◽  
The Common ◽  
Policy 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).

scholarly journals Active opportunist species as potential diagnostic markers for comparative tracking of complex marine ecosystem responses to global trends

2014 ◽  
Vol 71 (8) ◽  
pp. 2281-2292 ◽  
Author(s):  
Andrew Bakun
Keyword(s):  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Marine Ecosystem ◽  
Global Scale ◽  
Global Changes ◽  
Early Life Stages ◽  
Ecosystem Responses ◽  
Global Trends ◽  
Complex Adaptive ◽  
Species Groups

Abstract As it becomes ever clearer that on longer time scales marine ecosystems function as non-linear “complex adaptive systems”, potential consequences of global change become obscured within a maze of multiple possibilities. This essay attempts to route one pathway to a potentially more robust conceptual synthesis, employing the globally important example of anchovies and sardines as a model. Expressly, the anchovy emerges as an efficient specialist of neritic origin. In contrast, the sardine's oceanic-based adaptations equip it to deal with intermittent episodes of poorly productive conditions and to take advantage of associated reduction in predation pressure on early life stages of their offspring. Based on the overall synthesis, the nimble, wide-ranging, actively opportunistic sardine appears notably well equipped to deal with climate-related disruptions and dislocations and even to profit from their adverse effects on predators and competitors. Global-scale multispecies population synchronies in the 1970s to the mid-1980s suggest that a variety of different species types might be flagged for investigation as perhaps embodying similar “active opportunist” attributes. If so, events and anecdotes might, as global changes proceed, be viewed within a developing universal framework that could support increasingly effective transfers of experience and predictive foresight across different species groups and regional ecosystems.

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