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Landscape regularity modelling for environmental challenges in agriculture

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Abstract

In agricultural landscapes, methods to identify and describe meaningful landscape patterns play an important role to understand the interaction between landscape organization and ecological processes. We propose an innovative stochastic modelling method of agricultural landscape organization where the temporal regularities in land-use are first identified through recognized Land-Use Successions before locating these successions in landscapes. These time–space regularities within landscapes are extracted using a new data mining method based on Hidden Markov Models. We applied this methodological proposal to the Niort Plain (West of France). We built a temporo-spatial analysis for this case study through spatially explicit analysis of Land-Use Succession dynamics. Implications and perspectives of such an approach, which links together the temporal and the spatial dimensions of the agricultural organization, are discussed by assessing the relationship between the agricultural landscape patterns defined using this approach and ecological data through an illustrative example of bird nests.

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Notes

  1. Centre National de la Recherche Scientifique.

  2. Centre National de la Recherche Scientifique, Centre d’Etudes Biologiques de Chizé.

  3. http://www.loria.fr/~jfmari/App/

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Acknowledgments

This work was supported by the ANR-ADD-COPT project, the API-ECOGER project and the ANR-BiodivAgrim project. We thank the CNRS team in Chizé for their data records obtained from their “Niort Plain data base”. We thank Anne Mimet and the anonymous reviewers for their useful comments.

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Authors and Affiliations

  1. INRA, UR 055 SAD ASTER, 88500, Mirecourt, France

    El Ghali Lazrak & Marc Benoît

  2. UMR 7503 LORIA, U. Nancy 2, 54506, Vandœuvre-lès-Nancy, France

    Jean-François Mari

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  1. El Ghali Lazrak
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  2. Jean-François Mari
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  3. Marc Benoît
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Correspondence to El Ghali Lazrak.

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Lazrak, E.G., Mari, JF. & Benoît, M. Landscape regularity modelling for environmental challenges in agriculture. Landscape Ecol 25, 169–183 (2010). https://doi.org/10.1007/s10980-009-9399-8

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