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首页> 外文期刊>Global change biology >Phenology predicts the native and invasive range limits of common ragweed.
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Phenology predicts the native and invasive range limits of common ragweed.

机译:物候学预测普通豚草的自然和侵入范围限制。

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Accurate models for species' distributions are needed to forecast the progress and impacts of alien invasive species and assess potential range-shifting driven by global change. Although this has traditionally been achieved through data-driven correlative modelling, robustly extrapolating these models into novel climatic conditions is challenging. Recently, a small number of process-based or mechanistic distribution models have been developed to complement the correlative approaches. However, tests of these models are lacking, and there are very few process-based models for invasive species. We develop a method for estimating the range of a globally invasive species, common ragweed (Ambrosia artemisiifolia L.), from a temperature- and photoperiod-driven phenology model. The model predicts the region in which ragweed can reach reproductive maturity before frost kills the adult plants in autumn. This aligns well with the poleward and high-elevation range limits in its native North America and in invaded Europe, clearly showing that phenological constraints determine the cold range margins of the species. Importantly, this is a 'forward' prediction made entirely independently of the distribution data. Therefore, it allows a confident and biologically informed forecasting of further invasion and range shifting driven by climate change. For ragweed, such forecasts are extremely important as the species is a serious crop weed and its airborne pollen is a major cause of allergy and asthma in humans. Our results show that phenology can be a key determinant of species' range margins, so integrating phenology into species distribution models offers great potential for the mechanistic modelling of range dynamics.
机译:需要准确的物种分布模型来预测外来入侵物种的进展和影响,并评估由全球变化驱动的潜在范围变化。尽管传统上这是通过数据驱动的相关建模来实现的,但是将这些模型可靠地外推到新的气候条件中却具有挑战性。最近,已经开发了少量基于过程或机制的分布模型来补充相关方法。但是,缺乏对这些模型的测试,并且几乎没有针对入侵物种的基于过程的模型。我们开发了一种方法,用于根据温度和光周期驱动的物候模型来估计全球入侵物种(常见豚草(Ambrosia artemisiifolia L.))的范围。该模型预测,在秋季霜冻杀死成年植物之前,豚草可以达到生殖成熟的区域。这与北美原产地和入侵欧洲的极地和高海拔范围界限高度吻合,清楚地表明物候约束决定了该物种的寒冷范围边缘。重要的是,这是一个完全独立于分布数据做出的“前瞻”预测。因此,它可以对气候变化驱动下的进一步入侵和范围变化做出有信心且具有生物学依据的预测。对于豚草而言,这种预测极为重要,因为该物种是一种严重的农作物杂草,其空气中的花粉是导致人类过敏和哮喘的主要原因。我们的结果表明,物候学可能是决定物种范围裕度的关键因素,因此将物候学纳入物种分布模型为范围动力学的机械建模提供了巨大潜力。

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