Department of Ecology and Evolution, University of Lausanne, CH-1015 Lausanne, Switzerland.
Mol Ecol. 2011 Feb;20(4):692-705. doi: 10.1111/j.1365-294X.2010.04966.x. Epub 2010 Dec 22.
Functional connectivity affects demography and gene dynamics in fragmented populations. Besides species-specific dispersal ability, the connectivity between local populations is affected by the landscape elements encountered during dispersal. Documenting these effects is thus a central issue for the conservation and management of fragmented populations. In this study, we compare the power and accuracy of three methods (partial correlations, regressions and Approximate Bayesian Computations) that use genetic distances to infer the effect of landscape upon dispersal. We use stochastic individual-based simulations of fragmented populations surrounded by landscape elements that differ in their permeability to dispersal. The power and accuracy of all three methods are good when there is a strong contrast between the permeability of different landscape elements. The power and accuracy can be further improved by restricting analyses to adjacent pairs of populations. Landscape elements that strongly impede dispersal are the easiest to identify. However, power and accuracy decrease drastically when landscape complexity increases and the contrast between the permeability of landscape elements decreases. We provide guidelines for future studies and underline the needs to evaluate or develop approaches that are more powerful.
功能连接影响碎片化群体的人口统计学和基因动态。除了特定物种的扩散能力外，局部种群之间的连通性还受到扩散过程中遇到的景观元素的影响。因此，记录这些影响是保护和管理碎片化种群的核心问题。在这项研究中，我们比较了三种方法（偏相关、回归和近似贝叶斯计算）的有效性和准确性，这些方法使用遗传距离来推断景观对扩散的影响。我们使用随机个体基础模拟方法，对被不同扩散渗透性景观元素包围的碎片化种群进行模拟。当不同景观元素的渗透性之间存在强烈对比时，所有三种方法的有效性和准确性都很好。通过将分析限制在相邻的两个种群之间，可以进一步提高有效性和准确性。强烈阻碍扩散的景观元素最容易识别。然而，当景观复杂性增加且景观元素渗透性之间的对比减弱时，有效性和准确性会急剧下降。我们为未来的研究提供了指导，并强调需要评估或开发更强大的方法。
