Crops and climate change: progress, trends, and challenges in simulating impacts and informing adaptation
Crops and climate change: progress, trends, and challenges in simulating impacts and informing adaptation
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DOI：
10.1093/jxb/erp062
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发表时间：
2009-07-01
影响因子：
6.9
通讯作者：
Fraser, Evan
中科院分区：
文献类型：
--
作者：
Challinor, Andrew J.;Ewert, Frank;Fraser, Evan
对作物生产力与气候变化之间关系的评估依赖于模型和测量的结合。作为本次审查的一部分，这种关系的背景下，作物和气候模拟进行了讨论。这两种类型的模型连接的方法进行审查，主要集中在大面积作物建模技术。介绍了模拟气候变化对作物影响的最新进展，并讨论了这些方法在探索适应方案中的应用。具体进展包括集合模拟和对生物物理过程的更好理解。最后，讨论了与影响和适应研究相关的挑战。有人认为，政策和适应知识的生成不仅应基于已发表研究的综合，而且还应基于一个更具协同性和整体性的研究框架，其中包括：（一）对不确定性的可靠量化;（二）将侧重于基本进程的各种建模方法和观测结合起来的技术;（三）将各种建模方法和观测结合起来的技术;（四）将各种建模方法和观测结合起来的技术;（五）将各种建模方法和观测结合起来的技术;（六）将各种建模方法和观测结合起来的技术。以及（iii）明智地选择和校准模型，包括在适当复杂程度上进行模拟，以说明作物生产力的主要驱动因素，其中可能包括生物物理和社会经济因素。有人认为，这样一个框架将导致可靠的方法，将模拟与现实世界的适应办法联系起来，从而实际利用巨大的全球努力来了解和预测气候变化。
Assessments of the relationships between crop productivity and climate change rely upon a combination of modelling and measurement. As part of this review, this relationship is discussed in the context of crop and climate simulation. Methods for linking these two types of models are reviewed, with a primary focus on large-area crop modelling techniques. Recent progress in simulating the impacts of climate change on crops is presented, and the application of these methods to the exploration of adaptation options is discussed. Specific advances include ensemble simulations and improved understanding of biophysical processes. Finally, the challenges associated with impacts and adaptation research are discussed. It is argued that the generation of knowledge for policy and adaptation should be based not only on syntheses of published studies, but also on a more synergistic and holistic research framework that includes: (i) reliable quantification of uncertainty; (ii) techniques for combining diverse modelling approaches and observations that focus on fundamental processes; and (iii) judicious choice and calibration of models, including simulation at appropriate levels of complexity that accounts for the principal drivers of crop productivity, which may well include both biophysical and socio-economic factors. It is argued that such a framework will lead to reliable methods for linking simulation to real-world adaptation options, thus making practical use of the huge global effort to understand and predict climate change.