Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science.
Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science.
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DOI：
10.1016/j.agsy.2016.09.021
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发表时间：
2017-07
影响因子：
6.6
通讯作者：
Wheeler TR
中科院分区：
文献类型：
--
作者：
Jones JW;Antle JM;Basso B;Boote KJ;Conant RT;Foster I;Godfray HCJ;Herrero M;Howitt RE;Janssen S;Keating BA;Munoz-Carpena R;Porter CH;Rosenzweig C;Wheeler TR
我们回顾了农业系统科学的现状，特别关注农业系统模型的能力和局限性。我们讨论了与跨越田野、农场、景观、区域和全球空间尺度的五个不同用例相关的模型状态，并讨论了过去、当前和未来时间段的问题。多个学科的贡献在不同时空尺度的广泛农业系统模型应用方面取得了重大进展。尽管当前的农业系统模型具有用例所需的功能，但我们发现它们都有局限性并且需要改进。我们确定了所有用例的共同局限性，即 1）缺乏用于开发、评估和应用农业系统模型的数据；2）无法有效地将模型结果传达给社会的知识系统。我们认为，与概念理论或使用系统模型的可用方法中的差距相比，这些限制是进步的更大障碍。关于开放数据的新举措显示出解决数据问题的希望，但农业研究人员还需要进行文化变革，以确保用于解决各种用例的数据可用于未来的模型改进和应用。我们的结论是，不同目的的模型应用需要多个平台和多个模型。用例提供了一个有用的框架，用于考虑现有模型和数据的功能和限制。农业系统的所有组成部分都存在数据限制。模型的局限性也存在，在受约束的复杂系统中更为严重。用于为决策和政策提供信息的知识产品仍然非常有限。用例为模型评估和改进提供了重要的背景。需要更加重视农业系统的模型和系统分析。
We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and need to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data. Data limitations exist for all components of agricultural systems. Model limitations also exist, more severely in constrained, complex systems. Knowledge products for informing decisions and policy remain very limited. Use cases provide an important context for model evaluation and improvement. More emphasis is needed on models, systems analyses of agricultural systems.