Rosindell James, Cornell Stephen J
Institute of Integrative and Comparative Biology, University of Leeds, Leeds, West Yorkshire LS29JT, United Kingdom.
Ecology. 2009 Jul;90(7):1743-50. doi: 10.1890/08-0661.1.
We simulate species-area curves (SACs) using a spatially explicit neutral model. These display three distinct phases with the central phase being well approximated by a "power law" where species richness (S) is related to area (A) by S = cA(z). If seeds are normally distributed in space about their parent, the power law phase of the SAC is unrealistically narrow, and implausibly large speciation rates are required to fit empirical data. However, if dispersal follows a more realistic "fat-tailed" distribution (where long-distance dispersal events are more likely) the SACs fit the empirical data better, have a power law that holds for a much broader range of areas, and require a dramatically smaller speciation rate than when dispersal is normally distributed. Neutral models with biologically plausible dispersal parameters and speciation rates lead to empirically realistic SACs.
我们使用空间明确的中性模型来模拟物种 - 面积曲线(SACs)。这些曲线呈现出三个不同的阶段,其中中间阶段可以很好地用“幂律”来近似,即物种丰富度(S)与面积(A)的关系为S = cA(z)。如果种子在空间中围绕其亲本呈正态分布,那么SAC的幂律阶段就会不切实际地狭窄,并且需要极不合理的大物种形成率才能拟合经验数据。然而,如果扩散遵循更现实的“肥尾”分布(即长距离扩散事件更有可能发生),那么SACs能更好地拟合经验数据,具有在更广泛面积范围内成立的幂律,并且与扩散呈正态分布时相比,所需的物种形成率要小得多。具有生物学上合理的扩散参数和物种形成率的中性模型会导致符合经验现实的SACs。