Lattice models in ecology and social sciences
Lattice models in ecology and social sciences
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DOI：
10.1007/s11284-006-0163-0
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发表时间：
2006-04
影响因子：
2
通讯作者：
M. Nakamaru
中科院分区：
文献类型：
--
作者：
M. Nakamaru
在生态学和博弈论或社会科学中的其他模型中，在分析进化或种群动力学时经常假设个体之间的随机匹配或完全混合模型。在这个简单的假设下，制作和分析一个模型并不困难。然而，空间或网络结构的种群，包括格子模型和幂律网络，是更现实的许多生态和社会现象比完全混合模型。在这篇评论中，我将首先表明，一个格子模型可以是有用的，在调查邻里之间的相互作用的动态，不仅是植物和森林，而且动物和人类社会的影响。第二，格模型促进了恶意行为的进化，尽管众所周知格模型促进了合作的进化。最后，不同的社交网络会导致特征（如社会规范）以不同的速度传播。
Random matching between individuals, or the complete-mixing model, is often assumed in analyzing evolutionary or population dynamics in ecology and game theory or other models in social sciences. Making and analyzing a model is not difficult under this simple assumption. However spatial- or network-structured populations, including the lattice model and the power-law network, are more realistic for many ecological and social phenomena than the complete-mixing model. In this review, I will show first that a lattice model can be useful in investigating the effect of neighborhood interactions on the dynamics, not only of plants and forests, but also of animal and human societies. Second, the lattice model promotes the evolution of spiteful behavior, even though it is well-known that the lattice model promotes the evolution of cooperation. Finally, different social networks result in traits, such as social norms, spreading at different speeds.