Population growth and collapse in a multiagent model of the Kayenta Anasazi in Long House Valley

Axtell, Robert L.; Epstein, Joshua M.; Dean, Jeffrey; Gumerman, George J.; Swedlund, Alan C.; Harburger, Jason; Chakravarty, Shubha; Hammond, Ross A.; Parker, James G.; Parker, Miles T.

doi:10.1073/pnas.092080799

Cited by 316 publications

(217 citation statements)

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“…But models in various fields of application other than adaptive capacity are beginning to identify features of current systems that make the system more or less resilient, more or less likely to give rise to unpleasant futures (e.g. Axtell et al 2002, Moss et al 2001, Rouchier et al 2001. Given the inherent unpredictability of complex adaptive systems, it is unlikely that any model -ABM or EBM -will be able to foresee long range future events with a great degree of reliability (Bradbury 2002).…”

Section: Resultsmentioning

confidence: 99%

“…They were able to observe the system taking on complex properties -unpredictability in the movement of the agents, as well as emergent behavior in terms of the migration patterns of whole communities -given very little about the agents themselves that was complex. On the other hand, the researcher may want to investigate patterns emerging in real systems, either historical (Axtell et al 2002), present (Farmer 2000, Rouchie et al 2001, Tesfatsion 2001a, or future developments (Bonabeau 2002b, Moss and Schneider 2000, Moss 2002. For this, one needs data about the system: the agents, their relationships to each other, and the environment in which they operate.…”

Section: Agent Based Modeling As An Approach To Grasp Emergent Propermentioning

confidence: 99%

“…The agent based model, then, was able to show that the coordination achieved through the traditional system of priests and temples was in fact superior to that achieved by the central government. In another landmark example, researchers showed that the population growth, and more ominously the collapse occurring among the Anasazi native American tribe was the result not of extraordinary events, but rather of mundane interactions between a heterogeneous group of people in a constrained environment (Axtell et al 2002).…”

Section: The Puzzle Of Recurrent Failures To Adaptmentioning

confidence: 99%

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Agent Based Modeling and Adaptation to Climate Change

Patt¹,

Siebenhüner²

2005

VJH

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Agent Based Modeling and Adaptation to Climate Change* By Anthony Patt** and Bernd Siebenhüner*** Summary: Agent based modeling is a technique for simulating complex systems that allows the modeler to investigate both the potential for and the sources of emergent properties: behaviors of the system quite different from the behavior of any of the elements within it. Problems well suited to investigation by agent based models are those with many people solving a similar problem where their individual responses to the problem influence the choices that others make, where new technologies may emerge to assist them solve the problem, and where social dilemmas exist. These features are inherent in many problems of adaptation to climate change. Agent based modeling can not predict the future of a complex adaptive system -no method of modeling can -but it can offer insights into the relationship between features of current systems and the range of possible future adaptations that will be likely in response to climate change. Terms of use: Documents in EconStor may

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Section: Resultsmentioning

confidence: 99%

Section: Agent Based Modeling As An Approach To Grasp Emergent Propermentioning

confidence: 99%

Section: The Puzzle Of Recurrent Failures To Adaptmentioning

confidence: 99%

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Agent Based Modeling and Adaptation to Climate Change

Patt¹,

Siebenhüner²

2005

VJH

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“…Their application to food and nutrition security can provide fresh insights into the interconnectedness and interdependencies within as well as across sectors, scale, space, time, and jurisdiction, potentially identifying promising new strategies for single and/or system-level intervention. Of particular interest for a systems approach to food and nutrition security are system dynamics (SD) and agent-based modeling (ABM) (47)(48)(49)(50)(51)(52)(53)(54)(55).…”

Section: Complexity Of Food and Nutrition Securitymentioning

confidence: 99%

A systems science perspective and transdisciplinary models for food and nutrition security

Hammond

Dubé

2012

Proc. Natl. Acad. Sci. U.S.A.

183

143

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We argue that food and nutrition security is driven by complex underlying systems and that both research and policy in this area would benefit from a systems approach. We present a framework for such an approach, examine key underlying systems, and identify transdisciplinary modeling tools that may prove especially useful.complexity | agri-food | health | disease | environment N utrition is a fundamental human need, affecting health and well-being throughout the lifespan in myriad ways. A central concept in the study of human nutrition is food and nutrition security, which is typically defined as "when all people, at all times, have physical and economic access to sufficient, safe and nutritious food to meet their dietary needs and food preferences for an active and healthy life" (1). The absence of food and nutrition security can have significant consequences for individuals and for society, including malnutrition, obesity, disease, and poverty.Despite rapid growth in agricultural production over the past four decades, significant malnutrition persists. Average per-capita food consumption was below the recommended 2,200 kcal/d in 33 countries in 2003. Globally, more than 850 million people lack adequate access to food on a regular basis, with a third of these in East and Southeast Asia, another third in South Asia, and a quarter in sub-Saharan Africa. In sub-Saharan Africa, one of the most food-insecure regions, the number of hungry people has gone up by 20% since 1990; more than a third of the population is undernourished in such countries as Kenya and Tanzania. There are 126 million underweight children in the world and over 2 billion people who suffer from micronutrient deficiency (2-4).At the same time, there has been an alarming rise in obesity in the developed world (5, 6) and, increasingly, in the developing world as well (7-9). The obesity rate in the United States doubled between 1970 and 2000, to almost 30% (5); worldwide, nearly 1.5 billion people are now overweight or obese (9). Like malnutrition, obesity has significant implications for public health (10, 11) and health care costs (12). Obesity can coexist in the same populations as malnutrition, and it may be linked to the same forces that drive reductions in malnutrition (13, 14). Complexity of Food and Nutrition SecurityBoth phenomena, malnutrition and obesity, are manifestations of widespread food and nutrition insecurity. The determinants of this insecurity are complex. A primary driver of food security or insecurity is the agricultural food system. The agrifood system spans a series of interrelated processes, including production of raw food materials through farming and raising of livestock, processing and packaging for consumption, distribution, and utilization by consumers (15). These processes are affected by a range of influences, including diffusion of agricultural technology (16, 17), functioning of capital markets, infrastructure at both local and regional/global levels, organization of firms and supply chains, sociopolitical factors ...

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“…Initial models developed for the United States Southwest (94,95) tended to demonstrate that farmers in these uplands were exquisitely sensitive to precipitation-mediated variability in maize production before intensification of water-control technologies after ∼AD 1300.…”

Section: Climate and The Spread Of Farming In Asiamentioning

confidence: 99%

Twenty-first century approaches to ancient problems: Climate and society

Guedes

Crabtree

Bocinsky

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

112

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By documenting how humans adapted to changes in their environment that are often much greater than those experienced in the instrumental record, archaeology provides our only deep-time laboratory for highlighting the circumstances under which humans managed or failed to find to adaptive solutions to changing climate, not just over a few generations but over the longue durée. Patterning between climatemediated environmental change and change in human societies has, however, been murky because of low spatial and temporal resolution in available datasets, and because of failure to model the effects of climate change on local resources important to human societies. In this paper we review recent advances in computational modeling that, in conjunction with improving data, address these limitations. These advances include network analysis, niche and species distribution modeling, and agent-based modeling. These studies demonstrate the utility of deep-time modeling for calibrating our understanding of how climate is influencing societies today and may in the future.climate change | archaeology | computational modeling | agent-based modeling

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Population growth and collapse in a multiagent model of the Kayenta Anasazi in Long House Valley

Cited by 316 publications

References 10 publications

Agent Based Modeling and Adaptation to Climate Change

Agent Based Modeling and Adaptation to Climate Change

A systems science perspective and transdisciplinary models for food and nutrition security

Twenty-first century approaches to ancient problems: Climate and society

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