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Pushing precipitation to the extremes in distributed experiments: recommendations for simulating wet and dry years

机译:推动分布式实验中极端的降水:模拟湿旱短的建议

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Intensification of the global hydrological cycle, ranging from larger individual precipitation events to more extreme multiyear droughts, has the potential to cause widespread alterations in ecosystem structure and function. With evidence that the incidence of extreme precipitation years (defined statistically from historical precipitation records) is increasing, there is a clear need to identify ecosystems that are most vulnerable to these changes and understand why some ecosystems are more sensitive to extremes than others. To date, opportunistic studies of naturally occurring extreme precipitation years, combined with results from a relatively small number of experiments, have provided limited mechanistic understanding of differences in ecosystem sensitivity, suggesting that new approaches are needed. Coordinated distributed experiments (CDEs) arrayed across multiple ecosystem types and focused on water can enhance our understanding of differential ecosystem sensitivity to precipitation extremes, but there are many design challenges to overcome (e. g., cost, comparability, standardization). Here, we evaluate contemporary experimental approaches for manipulating precipitation under field conditions to inform the design of ` Drought-Net', a relatively low-cost CDE that simulates extreme precipitation years. A common method for imposing both dry and wet years is to alter each ambient precipitation event. We endorse this approach for imposing extreme precipitation years because it simultaneously alters other precipitation characteristics (i. e., event size) consistent with natural precipitation patterns. However, we do not advocate applying identical treatment levels at all sites -a common approach to standardization in CDEs. This is because precipitation variability varies > fivefold globally resulting in a wide range of ecosystem-specific thresholds for defining extreme precipitation years. For CDEs focused on precipitation extremes, treatments should be based on each site's past climatic characteristics. This approach, though not often used by ecologists, allows ecological responses to be directly compared across disparate ecosystems and climates, facilitating process-level understanding of ecosystem sensitivity to precipitation extremes.
机译:全球水文循环的强化,从更大的单独降水事件到更极端的多年干旱,有可能导致生态系统结构和功能的广泛改变。有了证据表明,极端降水量的发病率(统计学上从历史降水记录统治)正在增加,明确需要识别最容易受这些变化的生态系统,并理解为什么一些生态系统对极端的敏感性比其他生态系统更敏感。迄今为止,对自然发生的极端降水量的机会学研究,与相对少量的实验结果相结合,为生态系统敏感性的差异提供了有限的机械理解,这表明需要新的方法。协调分布式实验(CDES)跨越多种生态系统类型,并专注于水可以提高我们对差动生态系统敏感性的理解,以降低极端,但克服了许多设计挑战(例如,成本,可比性,标准化)。在这里,我们评估了在现场条件下操纵降水的现代实验方法,以告知“干旱网”的设计,这是一种相对低成本的CDE,用于模拟极端降水年。对干燥和潮湿的年份的常用方法是改变每个环境降水事件。我们赞同这种施加极端降水量的方法,因为它同时改变了与自然降水模式一致的其他降水特征(即,事件尺寸)。但是,我们不提倡在所有网站上应用相同的治疗水平 - 在CDES中的标准化的常见方法。这是因为降水可变性变化>五十倍地区,导致为定义极端降水量的广泛的生态系统特异性阈值。对于重点放射极端的CDES,治疗应基于每个网站的过去的气候特征。这种方法虽然不经常被生态学家使用,但在不同的生态系统和气候中允许直接与生态反应相比,促进对生态系统敏感性以降低极端的过程级别了解。

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