摘要翻译：
我们利用模糊认知映射(FCM)对8位浅湖生态领域科学家绘制的个体认知图进行扩充，建立了一个通用的浅湖生态系统模型。我们计算了个体认知图和集体认知图的图论指数。图论指数揭示了浅水湖泊生态系统的非线性动力学内部循环。生态过程是民主组织的，没有自上而下的等级结构。该模型的稳态条件是典型的浑浊型浅水湖泊生态系统，因为没有引起浑浊和清水状态转换的动态环境变化，只有动态扰动区才能维持清水状态。本文建立的模型反映了浅水湖泊的经验行为，包含了交替稳定状态理论的基本模型。此外，我们的模型扩展了基本模型，量化了联系的相对效应，并对其进行了扩展。在我们扩展的模型中，我们运行了4个模拟：收获沉水植物，养分减少，不减少养分的鱼类去除和生物营养。只有生物营养，包括去除鱼类和减少营养物质，才有可能将浑浊状态转变为清水状态。该模型的结构和关系以及管理模拟的结果得到了浅水湖泊生态系统实际野外研究的支持。因此，模糊认知映射方法使我们能够从整体上理解浅水湖泊生态系统的复杂结构，并基于该领域专家的隐性知识获得有效的通用模型。
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英文标题：
《A Cognitive Model of an Epistemic Community: Mapping the Dynamics of
  Shallow Lake Ecosystems》
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作者：
Can O. Tan and Uygar Ozesmi
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最新提交年份：
2005
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分类信息：

一级分类：Quantitative Biology        数量生物学
二级分类：Neurons and Cognition        神经元与认知
分类描述：Synapse, cortex, neuronal dynamics, neural network, sensorimotor control, behavior, attention
突触，皮层，神经元动力学，神经网络，感觉运动控制，行为，注意
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一级分类：Quantitative Biology        数量生物学
二级分类：Other Quantitative Biology        其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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英文摘要：
  We used fuzzy cognitive mapping (FCM) to develop a generic shallow lake ecosystem model by augmenting the individual cognitive maps drawn by 8 scientists working in the area of shallow lake ecology. We calculated graph theoretical indices of the individual cognitive maps and the collective cognitive map produced by augmentation. The graph theoretical indices revealed internal cycles showing non-linear dynamics in the shallow lake ecosystem. The ecological processes were organized democratically without a top-down hierarchical structure. The steady state condition of the generic model was a characteristic turbid shallow lake ecosystem since there were no dynamic environmental changes that could cause shifts between a turbid and a clearwater state, and the generic model indicated that only a dynamic disturbance regime could maintain the clearwater state. The model developed herein captured the empirical behavior of shallow lakes, and contained the basic model of the Alternative Stable States Theory. In addition, our model expanded the basic model by quantifying the relative effects of connections and by extending it. In our expanded model we ran 4 simulations: harvesting submerged plants, nutrient reduction, fish removal without nutrient reduction, and biomanipulation. Only biomanipulation, which included fish removal and nutrient reduction, had the potential to shift the turbid state into clearwater state. The structure and relationships in the generic model as well as the outcomes of the management simulations were supported by actual field studies in shallow lake ecosystems. Thus, fuzzy cognitive mapping methodology enabled us to understand the complex structure of shallow lake ecosystems as a whole and obtain a valid generic model based on tacit knowledge of experts in the field.
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PDF链接：
https://arxiv.org/pdf/q-bio/0509022