The landscape model: A model for exploring trade-offs between agricultural production and the environment.
The landscape model: A model for exploring trade-offs between agricultural production and the environment.
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DOI：
10.1016/j.scitotenv.2017.07.193
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发表时间：
2017-12-31
期刊：
影响因子：
--
通讯作者：
Whitmore AP
中科院分区：
文献类型：
--
作者：
Coleman K;Muhammed SE;Milne AE;Todman LC;Dailey AG;Glendining MJ;Whitmore AP
我们描述了一个模拟农业景观空间和时间相互作用的模型框架，可用于探索生产与环境之间的权衡，从而帮助确定可持续粮食生产问题的解决方案。在这里，我们关注的是景观中农业生产、水运动和养分流动的模型。我们根据两个长期实验的数据来验证这些模型，（第一个是连续的小麦实验，另一个是永久的草地实验），另一个是在孤立的集水区测量水和养分流动的实验。该模型对小麦产量（RMSE为20.3 ~ 28.6%）、籽粒氮（RMSE为21.3 ~ 42.5%）和磷（RMSE为20.2 ~ 29%，不含无氮样地）和土壤总有机碳（RMSE为3.1 ~ 13.8%）的模拟效果特别好，对水流量的模拟也很合理（RMSE为180.36和226.02%）。我们举例说明使用我们的模型框架来探索生产和营养损失之间的权衡。了解产量和环境之间的权衡对SI至关重要。景观模型有助于理解作物-土壤-水的相互作用。该模型是根据50年的两个长期实验数据验证的。根据North Wyke农场平台的空间显式数据验证模型。该模型对小麦产量、籽粒氮和籽粒磷的模拟效果较好。
We describe a model framework that simulates spatial and temporal interactions in agricultural landscapes and that can be used to explore trade-offs between production and environment so helping to determine solutions to the problems of sustainable food production. Here we focus on models of agricultural production, water movement and nutrient flow in a landscape. We validate these models against data from two long-term experiments, (the first a continuous wheat experiment and the other a permanent grass-land experiment) and an experiment where water and nutrient flow are measured from isolated catchments. The model simulated wheat yield (RMSE 20.3–28.6%), grain N (RMSE 21.3–42.5%) and P (RMSE 20.2–29% excluding the nil N plots), and total soil organic carbon particularly well (RMSE 3.1 − 13.8 %), the simulations of water flow were also reasonable (RMSE 180.36 and 226.02%). We illustrate the use of our model framework to explore trade-offs between production and nutrient losses. Understanding trade-offs between yield and environment is essential for SI. The Landscape Model aids the understanding of crop-soil-water interactions. Model validated against 50 years of data from two long-term experiments. Model validated against spatially-explicit data from the North Wyke farm platform. The model simulated wheat yield, grain N and grain P particularly well.
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影响因子：
2.8
作者：
Andrew, Izzadora K. S.;Storkey, Jonathan
通讯作者：
Storkey, Jonathan
影响因子：
6.5
作者：
Del Grosso, SJ;Mosier, AR;Ojima, DS
通讯作者：
Ojima, DS
DOI：
10.1073/pnas.0800437105
发表时间：
2008-10-21
影响因子：
11.1
作者：
Andam, Kwaw S.;Ferraro, Paul J.;Robalino, Juan A.
通讯作者：
Robalino, Juan A.
影响因子：
3.1
作者：
Bell, M. J.;Jones, E.;Sommer, M.
通讯作者：
Sommer, M.
影响因子：
6.3
作者：
Bell, V. A.;Kay, A. L.;Moore, R. J.
通讯作者：
Moore, R. J.