Galton-Watson过程和贝叶斯推断：一种小种群生存力研究的交钥匙方法
Galton-Watson process and bayesian inference: A turnkey method for the viability study of small populations
摘要：
1在生物多样性监测和保护管理中，需要准确预测灭绝时间。2. Galton-Watson过程是描述种群动态的经典随机模型。它的演化类似于矩阵种群模型，其中后代数量是随机的。灭绝概率，灭绝时间，丰度是众所周知的，并给出了明确的公式。与确定性模型相比，它可以应用于小群体。3模型的参数可以通过贝叶斯推断框架进行估计。这使得能够考虑非任意场景。4我们展示了如何将贝叶斯推断与Galton-Watson模型耦合提供几个特征：i）具有易于理解的参数的灵活建模方法ii）与经典矩阵人口模型（Leslie型模型）的兼容性iii）非计算方法，从而以更少的计算获得更多的信息iv）对场景，参数和模型的非任意选择。可以看出，它比经典的矩阵种群模型的生存能力问题更进一步。5为了说明这些特征，我们提供了两个例子的分析细节，其中一个是现实生活中的例子。
英文摘要：
1 Sharp prediction of extinction times is needed in biodiversity monitoring and conservation management. 2 The Galton-Watson process is a classical stochastic model for describing population dynamics. Its evolution is like the matrix population model where offspring numbers are random. Extinction probability, extinction time, abundance are well known and given by explicit formulas. In contrast with the deterministic model, it can be applied to small populations. 3 Parameters of this model can be estimated through the Bayesian inference framework. This enables to consider non-arbitrary scenarios. 4 We show how coupling Bayesian inference with the Galton-Watson model provides several features: i) a flexible modelling approach with easily understandable parameters ii) compatibility with the classical matrix population model (Leslie type model) iii) A non-computational approach which then leads to more information with less computing iv) a non-arbitrary choice for scenarios, parameters... It can be seen to go one step further than the classical matrix population model for the viability problem. 5 To illustrate these features, we provide analysis details for two examples whose one of which is a real life example.
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