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在整个美国大陆,生态系统生产力对降雨异常的非对称响应与年平均降雨量呈反比。

Asymmetric responses of ecosystem productivity to rainfall anomalies vary inversely with mean annual rainfall over the conterminous United States.

机构信息

Sorbonne Université, UMR 7619 METIS, Paris, France.

INRAE, Université de Bordeaux, UMR1391 ISPA, Villenave d'Ornon, France.

出版信息

Glob Chang Biol. 2020 Dec;26(12):6959-6973. doi: 10.1111/gcb.15345. Epub 2020 Sep 25.

DOI:10.1111/gcb.15345
PMID:32902073
Abstract

The CONterminous United States (CONUS) presents a large range of climate conditions and biomes where terrestrial primary productivity and its inter-annual variability are controlled regionally by rainfall and/or temperature. Here, the response of ecosystem productivity to those climate variables was investigated across different biomes from 2010 to 2018 using three climate datasets of precipitation, air temperature or drought severity, combined with several proxies of ecosystem productivity: a remote sensing product of aboveground biomass, an net primary productivity (NPP) remote sensing product, an NPP model-based product and four gross primary productivity products. We used an asymmetry index (AI) where positive AI indicates a greater increase of ecosystem productivity in wet years compared to the decline in dry years, and negative AI indicates a greater decline of ecosystem productivity in dry years compared to the increase in wet years. We found consistent spatial patterns of AI across the CONUS for the different products, with negative asymmetries over the Great Plains and positive asymmetries over the southwestern CONUS. Shrubs and, to a lesser extent, evergreen forests show a persistent positive asymmetry, whilst (natural) grasslands appear to have transitioned from positive to negative anomalies during the last decade. The general tendency of dominant negative asymmetry response for ecosystem productivity across the CONUS appears to be influenced by the negative asymmetry of precipitation anomalies. AI was found to be a function of mean rainfall: more positive AIs were found in dry areas where plants are adapted to drought and take advantage of rainfall pulses, and more negative AIs were found in wet areas, with a threshold delineating the two regimes corresponding to a mean annual rainfall of 200-400 mm/year.

摘要

美国本土(CONUS)呈现出大范围的气候条件和生物群落,其中陆地初级生产力及其年际变化受降雨和/或温度的区域性控制。在这里,使用三种降水、空气温度或干旱严重程度的气候数据集,结合几种生态系统生产力的代理指标,从 2010 年到 2018 年,研究了不同生物群落的生态系统生产力对这些气候变量的响应:地上生物量的遥感产品、净初级生产力(NPP)遥感产品、基于 NPP 模型的产品和四个总初级生产力产品。我们使用了不对称指数(AI),其中正的 AI 表示在湿润年份生态系统生产力的增加大于干旱年份的减少,而负的 AI 表示在干旱年份生态系统生产力的减少大于湿润年份的增加。我们发现,不同产品的 CONUS 都存在一致的 AI 空间模式,大平原地区存在负不对称,美国西南部地区存在正不对称。灌木,尤其是常绿林表现出持续的正不对称,而(天然)草原在过去十年中似乎已经从正异常转变为负异常。CONUS 生态系统生产力的普遍负不对称响应趋势似乎受到降水异常的负不对称影响。AI 是平均降雨量的函数:在植物适应干旱并利用降雨脉冲的干旱地区,发现了更积极的 AI,而在湿润地区,发现了更消极的 AI,两者之间的一个阈值对应于平均年降雨量为 200-400mm/年的两个地区。

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