Environmental Geography Group, Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Swiss Federal Research Institute WSL, Birmensdorf, Switzerland.
Glob Chang Biol. 2020 Mar;26(3):1045-1054. doi: 10.1111/gcb.14940. Epub 2020 Jan 11.
Climate-smart agriculture (CSA) and sustainable intensification (SI) are widely claimed to be high-potential solutions to address the interlinked challenges of food security and climate change. Operationalization of these promising concepts is still lacking and potential trade-offs are often not considered in the current continental- to global-scale assessments. Here we discuss the effect of spatial variability in the context of the implementation of climate-smart practices on two central indicators, namely yield development and carbon sequestration, considering biophysical limitations of suggested benefits, socioeconomic and institutional barriers to adoption, and feedback mechanisms across scales. We substantiate our arguments by an illustrative analysis using the example of a hypothetical large-scale adoption of conservation agriculture (CA) in sub-Saharan Africa. We argue that, up to now, large-scale assessments widely neglect the spatially variable effects of climate-smart practices, leading to inflated statements about co-benefits of agricultural production and climate change mitigation potentials. There is an urgent need to account for spatial variability in assessments of climate-smart practices and target those locations where synergies in land functions can be maximized in order to meet the global targets. Therefore, we call for more attention toward spatial planning and landscape optimization approaches in the operationalization of CSA and SI to navigate potential trade-offs.
气候智能型农业(CSA)和可持续集约化(SI)被广泛认为是应对粮食安全和气候变化相互关联挑战的高潜力解决方案。这些有前途的概念的实施仍然缺乏,并且在当前的大陆到全球规模评估中,潜在的权衡往往没有被考虑。在这里,我们讨论了在实施气候智能型实践的背景下,空间变异性对两个核心指标(即产量发展和碳固存)的影响,同时考虑了建议效益的生物物理限制、采用的社会经济和制度障碍以及跨尺度的反馈机制。我们通过使用假设在撒哈拉以南非洲大规模采用保护性农业(CA)的例子来说明分析,来证实我们的观点。我们认为,到目前为止,大规模评估广泛忽视了气候智能型实践的空间变化效应,导致对农业生产的共同效益和减缓气候变化潜力的夸大陈述。迫切需要在对气候智能型实践的评估中考虑空间变异性,并针对那些可以最大限度地发挥土地功能协同作用的地点,以实现全球目标。因此,我们呼吁在 CSA 和 SI 的实施中更加关注空间规划和景观优化方法,以应对潜在的权衡。