Climate Physics Group, Jet Propulsion Laboratory, California Institute of Technology, m/s 233-300, Pasadena, CA, 91109-8099, USA; Joint Institute for Regional Earth System Science & Engineering, University of California Los Angeles, 607 Charles E Young Drive East, Young Hall, Room 4242, Los Angeles, CA, 90095-7228, USA.
Glob Chang Biol. 2014 Jun;20(6):1955-67. doi: 10.1111/gcb.12567. Epub 2014 Apr 3.
Spanning 15% of the global ice-free terrestrial surface, agricultural lands provide an immense and near-term opportunity to address climate change, food, and water security challenges. Through the computationally informed breeding of canopy structural traits away from those of modern cultivars, we show that solutions exist that increase productivity and water use efficiency, while increasing land-surface reflectivity to offset greenhouse gas warming. Plants have evolved to maximize capture of radiation in the upper leaves, thus shading competitors. While important for survival in the wild, this is suboptimal in monoculture crop fields for maximizing productivity and other biogeophysical services. Crop progenitors evolved over the last 25 million years in an atmosphere with less than half the [CO2] projected for 2050. By altering leaf photosynthetic rates, rising [CO2] and temperature may also alter the optimal canopy form. Here using soybean, the world's most important protein crop, as an example we show by applying optimization routines to a micrometeorological leaf canopy model linked to a steady-state model of photosynthesis, that significant gains in production, water use, and reflectivity are possible with no additional demand on resources. By modifying total canopy leaf area, its vertical profile and angular distribution, and shortwave radiation reflectivity, all traits available in most major crop germplasm collections, increases in productivity (7%) are possible with no change in water use or albedo. Alternatively, improvements in water use (13%) or albedo (34%) can likewise be made with no loss of productivity, under Corn Belt climate conditions.
农业用地覆盖了全球无冰陆地表面的 15%，为应对气候变化、粮食和水安全挑战提供了巨大且迫在眉睫的机会。通过对冠层结构特征进行计算指导的培育，使其远离现代品种的特征，我们表明存在一些解决方案，可以提高生产力和水利用效率，同时增加地表反射率以抵消温室气体变暖。植物已经进化到最大限度地在顶部叶片中捕获辐射，从而遮蔽竞争对手。虽然这对于在野外生存很重要，但在最大化生产力和其他生物地球物理服务的单一种植作物田中，这并不是最优的。作物的祖先在过去的 2500 万年中进化，当时的大气中二氧化碳含量不到 2050 年预计的一半。通过改变叶片光合作用速率，不断上升的二氧化碳和温度也可能改变最佳冠层形态。在这里，我们以大豆为例，这是世界上最重要的蛋白质作物，通过将优化例程应用于微气象叶片冠层模型与光合作用稳态模型的链接，我们表明，在不增加资源需求的情况下，通过改变总冠层叶片面积、其垂直分布和角度分布以及短波辐射反射率，这些特性在大多数主要作物种质资源中都存在，提高生产力（7%）是可能的，而水的利用或反照率没有变化。或者，在玉米带气候条件下，同样可以提高水的利用效率（13%）或反照率（34%），而不损失生产力。
