The spatial limitations of current neutral models of biodiversity.
The spatial limitations of current neutral models of biodiversity.
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DOI：
10.1371/journal.pone.0014717
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发表时间：
2011-03-14
期刊：
影响因子：
3.7
通讯作者：
Rosindell J
中科院分区：
文献类型：
--
作者：
Etienne RS;Rosindell J
生物多样性和植物地理学的统一中性理论越来越多地被接受为群落组成和动态的信息零模型。它成功地产生了宏观生态模式，如物种-面积关系和物种多度分布。然而，所采用的模型作出了许多不切实际的辅助假设。例如，流行的空间隐式版本假设一个本地情节交换移民与一个大的panmictic区域源池。这种简单的结构允许严格测试其与数据的拟合。相比之下，空间显式模型假设后代只与父母相距有限的距离，但人们还不能检验它们与数据拟合的显著性。在这里，我们比较了空间显式和空间隐式模型，拟合最常用的隐式模型（有两个级别，本地和区域）的数据模拟最常用的空间显式模型（其中后代分布在他们的父母在网格上根据径向对称高斯或“肥尾”分布）。基于这些拟合，我们表示空间隐式参数的空间显式参数。这表明我们如何从空间隐式参数中获得空间显式参数的估计。然而，这些参数之间的关系没有直观的意义。此外，空间隐式模型通常比空间显式模型的模拟数据更好地拟合观测到的物种-多度分布。因此，目前的空间显式中性模型的描述能力有限。然而，我们的研究结果表明，一个胖尾巴的扩散内核似乎提高了拟合，这表明扩散内核，甚至胖尾巴应在未来的研究。我们的结论是，更先进的空间明确的模型和工具来分析它们需要开发。
The unified neutral theory of biodiversity and biogeography is increasingly accepted as an informative null model of community composition and dynamics. It has successfully produced macro-ecological patterns such as species-area relationships and species abundance distributions. However, the models employed make many unrealistic auxiliary assumptions. For example, the popular spatially implicit version assumes a local plot exchanging migrants with a large panmictic regional source pool. This simple structure allows rigorous testing of its fit to data. In contrast, spatially explicit models assume that offspring disperse only limited distances from their parents, but one cannot as yet test the significance of their fit to data. Here we compare the spatially explicit and the spatially implicit model, fitting the most-used implicit model (with two levels, local and regional) to data simulated by the most-used spatially explicit model (where offspring are distributed about their parent on a grid according to either a radially symmetric Gaussian or a ‘fat-tailed’ distribution). Based on these fits, we express spatially implicit parameters in terms of spatially explicit parameters. This suggests how we may obtain estimates of spatially explicit parameters from spatially implicit ones. The relationship between these parameters, however, makes no intuitive sense. Furthermore, the spatially implicit model usually fits observed species-abundance distributions better than those calculated from the spatially explicit model's simulated data. Current spatially explicit neutral models therefore have limited descriptive power. However, our results suggest that a fatter tail of the dispersal kernel seems to improve the fit, suggesting that dispersal kernels with even fatter tails should be studied in future. We conclude that more advanced spatially explicit models and tools to analyze them need to be developed.
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