摘要翻译：
在Lotka-Volterra格式的基础上，构造了一个与遗传进化的离散时间Penna模型类似的年龄结构种群的确定性遗传模型。研究表明，如果像Penna模型一样，遗传信息用群体中缺陷基因的分数来表示，那么在两个模型中，每个特定个体年龄的群体数用完全相同的年龄函数来表示。这给了我们一种新的可能性，不用使用详细的微观Penna模型来考虑多物种进化。我们讨论了捕食者-食饵系统的一个特例，它代表了一个由生活在该生态系统中的年龄结构物种消耗的有限能量资源组成的生态系统。然后，所考虑的种群中个体数量的增加取决于可利用的能量资源、种群中缺陷基因分布函数的形状和生育年龄。我们表明，这些参数决定了整个生态系统走向平衡的趋势。
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英文标题：
《Lotka-Volterra population model of genetic evolution》
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作者：
Miroslaw R. Dudek
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最新提交年份：
2007
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分类信息：

一级分类：Quantitative Biology        数量生物学
二级分类：Populations and Evolution        种群与进化
分类描述：Population dynamics, spatio-temporal and epidemiological models, dynamic speciation, co-evolution, biodiversity, foodwebs, aging; molecular evolution and phylogeny; directed evolution; origin of life
种群动力学；时空和流行病学模型；动态物种形成；协同进化；生物多样性；食物网；老龄化；分子进化和系统发育；定向进化；生命起源
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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：
  A deterministic model of an age-structured population with genetics analogous to the discrete time Penna model of genetic evolution is constructed on the basis of the Lotka-Volterra scheme. It is shown that if, as in the Penna model, genetic information is represented by the fraction of defective genes in the population, the population numbers for each specific individual's age are represented by exactly the same functions of age in both models. This gives us a new possibility to consider multi-species evolution without using detailed microscopic Penna model.   We discuss a particular case of the predator-prey system representing an ecosystem consisting of a limited amount of energy resources consumed by the age-structured species living in this ecosystem. Then, the increase in number of the individuals in the population under consideration depends on the available energy resources, the shape of the distribution function of defective genes in the population and the fertility age. We show that these parameters determine the trend toward equilibrium of the whole ecosystem.
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PDF链接：
https://arxiv.org/pdf/q-bio/0701031