Simulation scenarios of spatio-temporal arrangement of crops at the landscape scale

  • Authors:

  • M. S. Castellazzi;J. Matthews;F. Angevin;C. Sausse;G. A. Wood;P. J. Burgess;I. Brown;K. F. Conrad;J. N. Perry

  • Affiliations:

  • PIE Division, Rothamsted Research, West Common, Harpenden AL5 2JQ, UK and Macaulay Land Use Research Institute, Craigiebuckler, Aberdeen AB15 8QH, UK;PIE Division, Rothamsted Research, West Common, Harpenden AL5 2JQ, UK;INRA, UAR 1240 Eco-innov, F-78850 Thiverval-Grignon, France;Centre de Grignon, CETIOM, F-78850 Thiverval-Grignon, France;Natural Resources Department, Cranfield University, Cranfield MK43 0AL, UK;Natural Resources Department, Cranfield University, Cranfield MK43 0AL, UK;Macaulay Land Use Research Institute, Craigiebuckler, Aberdeen AB15 8QH, UK;PIE Division, Rothamsted Research, West Common, Harpenden AL5 2JQ, UK;PIE Division, Rothamsted Research, West Common, Harpenden AL5 2JQ, UK

  • Venue:
  • Environmental Modelling & Software
  • Year:
  • 2010

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Abstract

The spatial and temporal arrangement of crops is a conspicuous feature of rural landscapes. It has been identified as an important factor in many environmental issues, such as the coexistence of genetically modified (GM) and non-GM crops, and the mitigation of soil erosion. This paper examines a scenario-based approach for rapid generation and screening of crop allocations that meet user's constraints without requiring mechanistic modelling. LandSFACTS (Landscape Scale Functional Allocation of Crops Temporally and Spatially) is a software application specifically designed to simulate such crop arrangement scenarios, whilst ensuring both spatial and temporal coherence with regard to the initial constraints. The software uses an empirical approach to allocate crops to fields (polygons in vector format) over a sequence of years, using a stochastic process (Markov chains) and rule-based constraints. Crop rotations are represented by transition probabilities complemented by other temporal constraints such as return period or prohibited sequences. Further spatial and temporal constraints on crop arrangement can be applied through separation distances, yearly proportions, and the application of statistical tests. The software outputs a crop allocation solution with a crop for every field for every year, respecting all user-defined constraints; the range of potential solutions can then be explored through multiple model runs. Metrics based upon the difficulty of obtaining such an allocation from the initial constraints are also generated. A case study is provided to demonstrate the use of combined agronomic and environmental criteria for exploring GM crop coexistence at the landscape scale.