Abstract

Whether crop phenology changes are caused by change in managements or by climate change belongs to the category of problems known as detection-attribution. Three type of rice (early, late and single rice) in China show an average increase in Length of Growing Period (LGP) during 1991–2012: 1.0±4.8day/decade (±standard deviation across sites) for early rice, 0.2±4.5day/decade for late rice and 2.0±6.0day/decade for single rice, based on observations from 141 long-term monitoring stations. Positive LGP trends are widespread, but only significant (P<0.05) at 25% of early rice, 22% of late rice and 38% of single rice sites. We developed a Bayes-based optimization algorithm, and optimized five parameters controlling phenological development in a process-based crop model (ORCHIDEE-crop) for discriminating effects of managements from those of climate change on rice LGP. The results from the optimized ORCHIDEE-crop model suggest that climate change has an effect on LGP trends dependent on rice types. Climate trends have shortened LGP of early rice (−2.0±5.0day/decade), lengthened LGP of late rice (1.1±5.4day/decade) and have little impacts on LGP of single rice (−0.4±5.4day/decade). ORCHIDEE-crop simulations further show that change in transplanting date caused widespread LGP change only for early rice sites, offsetting 65% of climate change induced LGP shortening. The primary drivers of LGP change are thus different among the three types of rice. Management are predominant driver of LGP change for early and single rice. This study shows that complex regional variations of LGP can be reproduced with an optimized crop model. We further suggest that better documenting observational error and management practices can help reduce large uncertainties existed in attribution of LGP change, and future rice crop modelling in global/regional scales should consider different types of rice and variable transplanting dates in order to better account impacts of management and climate change.

Full Text
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