Causation without correlation: Parasite-mediated frequency-dependent selection and infection prevalence

Parasite-mediated selection is thought to maintain host genetic diversity for resistance. We might thus expect to find a strong positive correlation between host genetic diversity and infection prevalence across natural populations. Here, we used computer simulations to examine host–parasite coevolution in 20 simi-isolated clonal populations across a broad range of values for both parasite virulence and parasite fecundity. We found that the correlation between host genetic diversity and infection prevalence can be significantly positive for intermediate values of parasite virulence and fecundity. But the correlation can also be weak and statistically non-significant, even when parasite-mediated frequency-dependent selection is the sole force maintaining host diversity. Hence correlational analyses of field populations, while useful, might underestimate the role of parasites in maintaining host diversity., This is a computer simulation written in Excel.  It includes a data set from a representative run, assuming virulence was equal to 0.7 with a mean parasite fecunity equal to 15.  Virulence and parasite fecundity can be reset by the user (see usage notes).   , Directions for simulation

1) Download and open the .xlsm file.

2) A dialog box will pop up.  Click \"enable macro\"

3) The file will open, and a \"bootstrap\" dialog box will pop up.  Close the box.

4) To change parameter values, click on the \"data1\" tab.

5) You will see a list of parameter values on the left-hand side of the sheet.

6) We left the birth rate of uninfected hosts (bu) at 10, but it could be changed. 

7) To change the birth rate of infected hosts (bi), simply change the bold blue entry next to \"bi\".
     Virulence is calculated as 1 - (bi/bu). 

8) To change the mean realized fecundity of parasites, change \"MeanBeta\".

9) To change the Standard Deviation for the birth rate of uninfected hosts, change \"STD_bu\".

10) Other variables can be changed in the sim, such as the probability of infected (or uninfected) migrants, but we left them as in \"data1\" 

11) The simulation can be run at any time for a single generation by pressing \"control +\"

12) T...

寄生虫介导的选择（parasite-mediated selection）被认为是维持宿主抗病性遗传多样性的核心机制。据此我们推测，在自然种群中，宿主遗传多样性与感染率之间应存在显著的正相关关系。本研究通过计算机模拟，在20个近似隔离的克隆种群（clonal populations）中探究了宿主-寄生虫共演化（host–parasite coevolution）过程，测试了寄生虫毒力（parasite virulence）和寄生虫繁殖力（parasite fecundity）的广泛取值范围。结果显示，当寄生虫毒力和繁殖力处于中等水平时，宿主遗传多样性与感染率的相关系数可显著为正；但即便寄生虫介导的频率依赖选择（parasite-mediated frequency-dependent selection）是维持宿主多样性的唯一选择压力，二者的相关性也可能较弱且无统计学显著性。因此，尽管野外种群的相关性分析具有一定应用价值，但可能会低估寄生虫在维持宿主遗传多样性过程中的作用。

本模拟由Excel编写，包含一组代表性运行的数据集，该数据集假设寄生虫毒力为0.7，平均寄生虫繁殖力为15。用户可自行重置毒力与寄生虫繁殖力参数（详见使用说明）。

模拟操作指南如下：
1. 下载并打开该.xlsm格式文件。
2. 弹出对话框后，点击“启用宏（macro）”。
3. 文件加载完成后会弹出“自助法（bootstrap）”对话框，关闭该弹窗即可。
4. 如需修改参数值，点击“data1”工作表标签。
5. 工作表左侧将显示所有参数值列表。
6. 本研究中未修改未感染宿主的出生率（bu），将其固定为10，该参数亦可调整。
7. 如需修改感染宿主的出生率（bi），仅需更改“bi”旁的蓝色粗体条目即可。毒力计算公式为：1 - (bi/bu)。
8. 如需修改寄生虫的实际平均繁殖力，更改“MeanBeta”参数即可。
9. 如需修改未感染宿主出生率的标准差，更改“STD_bu”参数即可。
10. 模拟中还可修改其他变量，例如感染（或未感染）宿主的迁移概率，本研究中均保留了“data1”中的默认设置。
11. 按下“Ctrl++”快捷键，可随时运行单代模拟。
12. （原文此处截断）