农业生态系统间生产模式和用水效率的差异

IF 8 1区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES
Olivia L. Hajek , Nicole E. Kaplan , Shefali Azad , Philip A. Fay , Makki Khorchani , Amanda M. Nelson , Adam P. Schreiner-McGraw , Lori J. Abendroth , Claire Baffaut , John Baker , Brandon T. Bestelmeyer , Elizabeth H. Boughton , Dawn M. Browning , Bryan R. Carlson , Michel A. Cavigelli , Patrick E. Clark , Curtis Dell , Yuxi Guo , John Hendrickson , David Huggins , David L. Hoover
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引用次数: 0

摘要

在整个农业生态系统中,水是初级生产的关键驱动力,而降水与生产之间的关系(即水利用效率;水分利用效率(WUE)是评价农业生态系统对水分可利用性变化的适应能力的重要指标。虽然这种关系在相对不受管理的本地生态系统中已经得到了很好的表征,但缺乏跨越不同农业生态系统和气候梯度的跨站点综合。我们利用美国农业部的长期农业生态系统研究(LTAR)网络,在一系列广泛的气候条件和农业生态系统中评估年降水量与地上净初级产量(ANPP)之间的关系,这些气候条件和农业生态系统代表了原生牧场、农田和牧场以及各种管理强度。我们利用了15个站点的长期ANPP数据(平均17年),跨越了大降水梯度(265 - 1347 mm yr - 1)。在不同的降水梯度上,年降水量与生产力呈正相关;然而,这种非线性模式与本地生态系统不同,并因农业生态系统类型而异。牧场ANPP与年降水量呈强耦合关系,每100 mm降水增加近20%。按光合途径和作物类型分组的作物敏感性显著降低,但农田和牧场的敏感性显著降低。在这些敏感性模式背后,是不同农业生态系统间总体ANPP的巨大差异;尽管降水梯度存在重叠,但农田的ANPP比牧场高6.7倍,比牧场高2.6倍。虽然农业生态系统类型反映了大陆尺度上降水-生产关系的大部分变异性,但了解降水敏感性的更细微差异对于确定生产脆弱性和适应不断变化的水资源至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Variation in patterns of production and water-use efficiency among agroecosystems

Variation in patterns of production and water-use efficiency among agroecosystems
Across agroecosystems, water is a key driver of primary production, and the relationship between precipitation and production (i.e., water-use efficiency; WUE) provides an important indicator for evaluating agroecosystem resilience to changes in water availability. While this relationship has been well-characterized in relatively unmanaged, native ecosystems, cross-site syntheses spanning diverse agroecosystems and climate gradients are lacking. We leveraged the USDA's Long-Term Agroecosystem Research (LTAR) network to assess the relationship between annual precipitation and aboveground net primary production (ANPP) across an extensive set of climate conditions and agroecosystems, representing native rangelands, croplands, and pasturelands and various management intensities. We utilized long-term ANPP data (mean = 17 years) from fifteen sites spanning a large precipitation gradient (265 to 1347 mm yr−1). We observed a positive relationship between annual precipitation and productivity across precipitation gradients; however, this nonlinear pattern differed from native ecosystems and varied by agroecosystem type. Rangeland ANPP was strongly coupled to annual precipitation, increasing nearly 20% for every 100 mm of precipitation. Croplands and pasturelands showed significantly decreased sensitivity, although grouping crops by photosynthetic pathway and crop type revealed some significant patterns. Underlying these patterns in sensitivity were large differences in overall ANPP among agroecosystems; cropland ANPP was up to 6.7-fold greater than rangelands and 2.6-fold greater than pasturelands, despite overlapping precipitation gradients. While agroecosystem type captured much of the variability in the precipitation-production relationship at the continental scale, understanding the more subtle differences in precipitation sensitivities will be fundamental for identifying production vulnerabilities and adapting to changing water resources.
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来源期刊
Science of the Total Environment
Science of the Total Environment 环境科学-环境科学
CiteScore
17.60
自引率
10.20%
发文量
8726
审稿时长
2.4 months
期刊介绍: The Science of the Total Environment is an international journal dedicated to scientific research on the environment and its interaction with humanity. It covers a wide range of disciplines and seeks to publish innovative, hypothesis-driven, and impactful research that explores the entire environment, including the atmosphere, lithosphere, hydrosphere, biosphere, and anthroposphere. The journal's updated Aims & Scope emphasizes the importance of interdisciplinary environmental research with broad impact. Priority is given to studies that advance fundamental understanding and explore the interconnectedness of multiple environmental spheres. Field studies are preferred, while laboratory experiments must demonstrate significant methodological advancements or mechanistic insights with direct relevance to the environment.
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