4.7 Article

Climate-driven simulation of global crop sowing dates

Journal

GLOBAL ECOLOGY AND BIOGEOGRAPHY
Volume 21, Issue 2, Pages 247-259

Publisher

WILEY
DOI: 10.1111/j.1466-8238.2011.00678.x

Keywords

Agricultural management; crop calendars; global crop modelling; global sowing dates; major field crops; planting dates; temperature and precipitation seasonality

Funding

  1. International Food Policy Research Institute [6012001]
  2. International Livestock Research Institute [81102850]
  3. German Federal Ministry for Economic Cooperation and Development

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Aim To simulate the sowing dates of 11 major annual crops at the global scale at high spatial resolution, based on climatic conditions and crop-specific temperature requirements. Location Global. Methods Sowing dates under rainfed conditions are simulated deterministically based on a set of rules depending on crop-and climate-specific characteristics. We assume that farmers base their timing of sowing on experiences with past precipitation and temperature conditions, with the intra-annual variability being especially important. The start of the growing period is assumed to be dependent either on the onset of the wet season or on the exceeding of a crop-specific temperature threshold for emergence. To validate our methodology, a global data set of observed monthly growing periods (MIRCA2000) is used. Results We show simulated sowing dates for 11 major field crops world-wide and give rules for determining their sowing dates in a specific climatic region. For all simulated crops, except for rapeseed and cassava, in at least 50% of the grid cells and on at least 60% of the cultivated area, the difference between simulated and observed sowing dates is less than 1 month. Deviations of more than 5 months occur in regions characterized by multiple-cropping systems, in tropical regions which, despite seasonality, have favourable conditions throughout the year, and in countries with large climatic gradients. Main conclusions Sowing dates under rainfed conditions for various annual crops can be satisfactorily estimated from climatic conditions for large parts of the earth. Our methodology is globally applicable, and therefore suitable for simulating sowing dates as input for crop growth models applied at the global scale and taking climate change into account.

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