5/10/2021 0 Comments Hundredth Rare Download
Indeed, there is a critical common point between these expanding and non-expanding dynamics: they change their inner structure and the spatial relationships between their constitutive entities.
Hundredth Rare Download View PublicationDownload View publication Copy reference Copy caption Embed figure Landscape states of various scenarios.Examples of landscape scenarios for Lestolet crop successions at the hundredth iteration of each simulation with: random ( A ), intensive dairy and beef livestock production ( B ), extensive dairy and beef livestock production ( C ), hog production ( D ) systems and context-dependent random rotations ( E ).Wheat (brown), Maize (yellow) and temporary Grassland (green) land covers are highlighted on a (black) unchanged background.Overview 23 farms of the Lestolet basin, located in cartographic coordinates and using a colour scale (F). ![]() Christophe Godin Patchy landscapes driven by human decisions andor natural forces are still a challenge to be understood and modelled. No attempt has been made up to now to describe them by a coherent framework and to formalize landscape changing rules. Overcoming this lacuna was our first objective here, and this was largely based on the notion of Rewriting Syste. Cite Download full-text Contexts in source publication Context 1. Quantified dynamics of landscape compositions. The three land cover proportions (left-hand side) and grassland appearance frequencies (right-hand side) of the Lestolet during the four hundred-year long landscape scenarios detailed in figure 2. Furthermore, unit changes are context-dependent (or context- independent) when they involve the neighbourhood relationships to be updated. Here, we chose to illustrate three of these four classes of landscape unit changes, with an emphasis on the most common one: scenarios B, C, and D concern compositional changes without context dependency. Scenarios E and G are context-dependent, for either compositional or configurational landscape dynamics. Formalization and simulation stages were successful in modelling such complex dynamics in all cases (Fig. Hence, we are confident that RS would be adequately efficient to model a large panel of landscape dynamics. For example, more complicated rules, adapted to other agricultural, forested or peri- urban landscapes may be conveniently defined and modelled through RS. At the same time, we would also need a less empirical way to set priorities for the rules, a goal outside the scope of this paper. A distinctive feature of RS formalisms is that they give rise to a generic class of programming languages with a potential for use in specifying landscape models. This property of RS made it possible to construct a generic simulation software (here called DYPAL) that possesses the capacity to model a large variety of landscape dynamics. In particular, RS handles both Markovian and non- Markovian dynamics that are commonly found in man-made landscapes 5,24. RS is thus able to manage classical Markovian dynamics such as transition probability between land covers or other hidden-Markov-chain approaches 9,34, as well as more complicated non-linear processes such as sharp vegetation transitions undergoing natural or anthropogenic perturbations. Although it was not our intention here to prove this assertion, it is always possible to add a sharp rule starting at a specific iteration of the simulation. Hence, RS offers the opportunity to formalize land cover and land use changes that are most of the time modelled without any formalization. The majority of currently known landscape models indeed are inefficient to analyse the coherency and the properties of the changes they allow 6. Therefore, we need a coherent and self-sustaining approach able to capture a wide range of landscape units (polygons, polylines.) and a high diversity of dynamics (Markovian, non-Markovian.). We should not be intimidated by the apparent differences between the growing structures of plants to which RS have been applied and the stable boundary of a dynamic patchy landscape.
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