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- Mathieu, Jordane A.; Aires, Filipe
- Agricultural and forest meteorology 2018 v.253-254 pp. 15-30
- coasts; corn; crop yield; meteorological data; monitoring; prediction; statistical models; temperature; yield forecasting; Virginia
- ... Weather has a major impact on agriculture. Statistical models have been used to estimate or forecast crop yield from weather information. In this paper, a general statistical framework is developed in order to rank and quantify the information content of weather information. The methodology is tested over the US, for corn yield. The weather sensitivity of different corn production areas is first a ...
- Meng, Fandong; Suonan, Ji; Zhang, Zhenhua; Wang, Shiping; Duan, Jichuang; Wang, Qi; Li, Bowen; Luo, Caiyun; Jiang, Lili; Zhang, Lirong; Liu, Peipei; Renzeng, Wangmu; Lv, Wangwang; Wang, Zhezhen; Tsechoe, Dorji; Du, Mingyuan
- Agricultural and forest meteorology 2018 v.253-254 pp. 31-37
- climate change; cooling; flowering; functional diversity; models; moieties; phenology; prediction; regression analysis; species diversity; spring; summer; temperature; China
- ... Lack of understanding of how plant diversity of different flowering functional groups mediates response patterns of community phenophases to climate change limits our ability to predict future phenology. We used reciprocal transplant experiments across four elevations (i.e., 3200, 3400, 3600 and 3800 m) on the Tibetan Plateau for three years to investigate how temperature change (i.e., warming and ...