Tradeoffs between the strength of conformity and number of conformists in variable environments
Tradeoffs between the strength of conformity and number of conformists in variable environments
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DOI：
10.1016/j.jtbi.2013.04.023
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发表时间：
2013-09-07
影响因子：
2
通讯作者：
Laland, Kevin N.
中科院分区：
文献类型：
--
作者：
Kandler, Anne;Laland, Kevin N.
生物体通常通过学习策略对环境变化做出反应，从而增强在可变和不断变化的条件下的适应性。但是，对于暴露在这些条件下的人群，我们应该期待哪些策略呢？我们通过开发一个数学模型来解决这个问题，该模型指定了在时间和空间变化的环境中，个人和社会学习策略的不同混合对不同文化变体频率的影响。假设不同的文化变体对不同的环境条件有不同的适应能力，我们就能够评估哪种学习策略的混合能最大限度地提高群体的平均适应度。我们发现，即使在快速变化的环境中，仍有很大一部分人会一直参与社会学习。在这些环境中，最高的适应水平是通过相对较高的个人学习比例和强烈的从众偏见来实现的。我们在群体中社会学习的比例与从众的强度之间建立了负相关关系：强从众需要较少的从众者（即更大的个体学习比例），而许多从众者只有在从众传播较弱时才会出现。对文化多样性的调查表明，在频繁变化的环境中，高水平的适应需要高水平的文化多样性。最后，我们展示了如何将开发的数学框架应用于文化特征的使用或发生数据的时间序列。使用近似贝叶斯计算，我们能够推断出有关潜在学习过程的信息，这些信息可能会产生数据集中观察到的变化模式。(C) 2013 Elsevier Ltd.版权所有。
Organisms often respond to environmental change phenotypically, through learning strategies that enhance fitness in variable and changing conditions. But which strategies should we expect in population exposed to those conditions? We address this question by developing a mathematical model that specifies the consequences of different mixtures of individual and social learning strategies on the frequencies of different cultural variants in temporally and spatially changing environments. Assuming that alternative cultural variants are differently well-adapted to diverse environmental conditions, we are able to evaluate which mixture of learning strategies maximises the mean fitness of the population. We find that, even in rapidly changing environments, a high proportion of the population will always engage in social learning. In those environments, the highest adaptation levels are achieved through relatively high fractions of individual learning and a strong conformist bias. We establish a negative relationship between the proportion of the population learning socially and the strength of conformity operating in a population: strong conformity requires fewer conformists (i.e. larger proportion of individual learning), while many conformists can only be found when conformist transmission is weak. Investigations of cultural diversity show that in frequently changing environments high levels of adaptation require high level of cultural diversity. Finally, we demonstrate how the developed mathematical framework can be applied to time series of usage or occurrence data of cultural traits. Using Approximate Bayesian Computation we are able to infer information about the underlying learning processes that could have produced observed patterns of variation in the dataset. (C) 2013 Elsevier Ltd. All rights reserved.