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Mechanisms of long-distance dispersal of seeds by wind

机译:种子长距离散播风的机理

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Long-distance dispersal (LDD) is central to species expansion following climate change, re-colonization of disturbed areas and control of pests. The current paradigm is that the frequency and spatial extent of LDD events are extremely difficult to predict. Here we show that mechanistic models coupling seed release and aerodynamics with turbulent transport processes provide accurate probabilistic descriptions of LDD of seeds by wind. The proposed model reliably predicts the vertical distribution of dispersed seeds of five tree species observed along a 45-m high tower in an eastern US deciduous forest. Simulations show that uplifting above the forest canopy is necessary and sufficient for LDD, hence, they provide the means to define LDD quantitatively rather than arbitrarily. Seed uplifting probability thus sets an upper bound on the probability of long-distance colonization. Uplifted yellow poplar seeds are on average lighter than seeds at the forest floor, but also include the heaviest seeds. Because uplifting probabilities are appreciable (as much as 1-5%), and tree seed crops are commonly massive, some LDD events will establish individuals that can critically affect plant dynamics on large scales.
机译:长距离散布(LDD)对于气候变化,受干扰地区的重新定殖和害虫控制之后的物种扩展至关重要。当前的范例是,LDD事件的频率和空间范围很难预测。在这里,我们显示了将种子释放和空气动力学与湍流传输过程耦合在一起的力学模型提供了风对种子LDD的准确概率描述。提出的模型可靠地预测了在美国东部落叶林中沿着45米高的塔楼观察到的5种树种的分散种子的垂直分布。模拟表明,对于LDD而言,在林冠上方抬高是必要且充分的,因此,它们提供了定量而非任意定义LDD的方法。因此,种子提起的可能性为长距离定殖的可能性设定了上限。扬起的黄杨种子平均比森林地面的种子轻,但也包括最重的种子。因为提升的概率是可观的(高达1%至5%),并且树木种子作物通常很庞大,所以某些LDD事件将建立个体,从而严重影响植物的动态。

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