Spatial sensitivity of maize gene-flow to landscape pattern: a simulation approach
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Pollen dispersal is a critical process defining connectivity among plant populations. In the context of genetically modified (GM) crops in conventional agricultural systems, strategies based on spatial separation are promoted to reduce functional connectivity between GM and non-GM crop fields. Field experiments as well as simulation studies have stressed the dependence of maize gene flow on distances between source and receptor fields and on their spatial configuration. However, the influence of whole landscape patterns is still poorly understood. Spatially explicit models, such as MAPOD-maize, are thus useful tools to address this question. In this paper we developed a methodological approach to investigate the sensitivity of cross-pollination rates among GM and non-GM maize in a landscape simulated with MAPOD-maize. The influence of landscape pattern on model output was studied at the landscape and field scales, including interactions with other model inputs such as cultivar characteristics and wind conditions. At the landscape scale, maize configuration (proportion of and spatial arrangement in a given field pattern) was shown to be an important factor influencing cross-pollination rate between GM and non-GM maize whereas the effect of the field pattern itself was lower. At the field scale, distance to the nearest GM maize field was confirmed as a predominant factor explaining cross-pollination rate. The metrics describing the pattern of GM maize in the area surrounding selected non-GM maize fields appeared as pertinent complementary variables. In contrast, field geometry and field pattern resulted in little additional information at this scale.
KeywordsCross-pollination Global sensitivity analysis Landscape metrics Multi-scale analysis Pollen dispersal
We thank the Institute for the Protection and Security of the Citizen (Joint Research Centre of the European Union) and AUP-ONIGC for providing the maps of actual landscapes. We are very grateful to Mathieu Leclaire for his assistance with using MAPOD and to Mickael Corson for English corrections. This work was supported by the research program “Impact des OGM” (2002–2006) funded by the French Ministry of Research and by the European project SIGMEA (Contract no. 502981).
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