2016
DOI: 10.1007/s00477-016-1215-9
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Contribution of climatic and technological factors to crop yield: empirical evidence from late paddy rice in Hunan Province, China

Abstract: Climatic and technological factors are two remarkable aspects that are thought to contribute to crop yield change. However, the most significant factors and their contribution rate remain debatable. Selecting Hunan Province, which is one of the largest paddy rice producing regions in China as the research area, the marginal contributions of climatic and technological factors to late paddy yield change are estimated using a county-level panel data regression model with explicit consideration of technological va… Show more

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Cited by 15 publications
(12 citation statements)
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References 69 publications
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“…These results agree with previous studies and show that linear models have skill in reproducing observed yields. In contrast withWang et al (2016) this study finds that the inclusion of fertiliser in the linear models is significant for rice in China.As discussed in Lobell (2013) the quality of the linear model outputs are highly dependent on the inputs, in this study the models are limited by the effectively country level nature of the fertiliser and yield values and by the single planting and harvest date which was used for all years. This means the models do not account for early or late planting or harvest which could be a response to a change in the seasonal meteorology.…”
contrasting
confidence: 98%
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“…These results agree with previous studies and show that linear models have skill in reproducing observed yields. In contrast withWang et al (2016) this study finds that the inclusion of fertiliser in the linear models is significant for rice in China.As discussed in Lobell (2013) the quality of the linear model outputs are highly dependent on the inputs, in this study the models are limited by the effectively country level nature of the fertiliser and yield values and by the single planting and harvest date which was used for all years. This means the models do not account for early or late planting or harvest which could be a response to a change in the seasonal meteorology.…”
contrasting
confidence: 98%
“…ple linear models improves the representation of crop yields recorded in a 49 year dataset (Princeton) or a 31 year dataset (WFDEI). Similar linear models have been used in several previous studies at multiplesacles (Estes et al, 2013; Hernandez-Barrera et al, 2016; Lobell and Burke, 2010;Wang et al, 2016;Zhou and Wang, 2015). These results agree with previous studies and show that linear models have skill in reproducing observed yields.…”
supporting
confidence: 90%
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“…ET and GPP are sensitive to climate and human interference (Bai et al, 2014;Sun et al, 2016;Zhang et al, 2013). The interactions between climate change and human activities are quite complicated and difficult to segregate, especially in ago-ecosystem (Lobell et al, 2011;Wang et al, 2016), which may affect the implementation of management practices. Separating and quantifying the contributions of climate change and human activities to ET and GPP trends is essential for understanding the impacts of climatic factors on water consumption, carbon sequestration and adaptation strategies.…”
Section: Introductionmentioning
confidence: 99%
“…The linear models use a design that has been used in several previous studies (Estes et al, 2013;Lobell and Burke, 2010;Wang et al, 2016;Parkes et al, 2017). The models in this study use the robust linear fitting tools in MATLAB (Holland and Welsch, 1977) that are less sensitive to outliers than least-squares fitting.…”
Section: Linear Modelsmentioning
confidence: 99%