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

• Published in: Environmental modelling & software : with environment data news Vol. 25; no. 12; pp. 1881 - 1889
• Main Authors: Castellazzi, M.S., Matthews, J., Angevin, F., Sausse, C., Wood, G.A., Burgess, P.J., Brown, I., Conrad, K.F., Perry, J.N.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2010; Elsevier
• Subjects: Allocations; Coexistence; Computer programs; Computer simulation; Criteria; Crop allocation; Crop patterns; Crops; Environmental Sciences; GM crops; Humanities and Social Sciences; Landscape scale; Landscapes; Life Sciences; Mathematical models; Modelling; Scenarios; Software; Spatio-temporal modelling; Temporal logic; Crop patterns; Crop allocation; Landscape scale; Spatio-temporal modelling; Scenarios; Coexistence; Criteria; GM crops; transgenic maize; distance; criteria; rotation; spatio temporal modelling; crop allocation; tool; crop pattern; COEXISTENCE; scenario; decision-making; landscape scale; gene-flow; gm crop; model; échelle d'étude; agricultural landscape
• ISSN: 1364-8152; 1873-6726
• DOI: 10.1016/j.envsoft.2010.04.006

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.