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From Molecules To Landscapes: Rule-based FSPMs in the Language XL Winfried Kurth

From Molecules To Landscapes: Rule-based FSPMs in the Language XL Winfried Kurth Brandenburg University of Technology at Cottbus, Chair for Graphics Systems. Strengths and weaknesses of traditional approaches in plant modelling Relational Growth Grammars (RGGs)

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From Molecules To Landscapes: Rule-based FSPMs in the Language XL Winfried Kurth

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  1. From Molecules To Landscapes: Rule-based FSPMs in the Language XL Winfried Kurth Brandenburg University of Technology at Cottbus, Chair for Graphics Systems

  2. Strengths and weaknesses of traditional approaches in plant modelling • Relational Growth Grammars (RGGs) • as a generic tool on a formal level • 3. The language XL • 4. Future perspectives Cottbus, 10. 3. 2008

  3. 1. Strengths and weaknesses of traditional approaches in plant modelling • Challenges: • connection of structure and function in a coherent model framework • bridging the gap between different scales Cottbus, 10. 3. 2008

  4. GEOINFORMATICS bio-/geosphere region ecosystem population individual organ tissue cell organell / genome molecule BIOINFORMATICS / SYSTEMS BIOLOGY Cottbus, 10. 3. 2008

  5. GEOINFORMATICS bio-/geosphere region ecosystem population individual organ tissue cell organell / genome molecule ECOLOGICAL INFORMATICS BIOINFORMATICS / SYSTEMS BIOLOGY  Transfer of the Systems Biology viewpoint to higher scale levels Cottbus, 10. 3. 2008

  6. Tools for modelling and simulation: • (a) classical PBM (process-based models) • pools of substrates in compartments • fluxes between pools Example: STELLA flowcharts

  7. mathematical formalisms: • qualitative: Petri nets • quantitative: systems of differential equations • tools: • - numerics software • - graphical modelling environments (e.g., STELLA) Cottbus, 10. 3. 2008

  8. PBM – drawbacks: • spatial structure often poorly represented Cottbus, 10. 3. 2008

  9. PBM – drawbacks: • spatial structure often poorly represented • no representation of the objects with which the user • really works Cottbus, 10. 3. 2008

  10. PBM – drawbacks: • spatial structure often poorly represented • no representation of the objects with which the user • really works • parameters partially difficult to measure and to interpret Cottbus, 10. 3. 2008

  11. (b) structural models • entities: organs / modules • (biologically senseful and visualizable entities) • effects of interaction occur emergently • parameters: relatively few, measurable barley model (Buck-Sorlin et al. 2005) Cottbus, 10. 3. 2008

  12. (b) structural models • entities: organs / modules • (biologically senseful and visualizable entities) • effects of interaction occur emergently • parameters: relatively few, measurable most important approach from computer science for this type of models (until recently): Lindenmayer systems (L-systems) Cottbus, 10. 3. 2008

  13. Examples of L-system based plant models: K. 1998, 1999 Prusinkiewicz & Lindenmayer 1990

  14. Applications: virtual plant structures as a basis for simulations, e.g., light interception in a tree stand (Knyazikhin, Ibrom, K. 1997) water flow in a tree (Früh & K. 1999)

  15. structure has impact on function – example of xylem sap flow (Früh & K. 1999) spruce (L-system model) spruce (3D measurement) Thuja (3D measurement) Cottbus, 10. 3. 2008

  16. structural models – drawbacks: • no (or very sparse) taking into acount of the functional aspects of organisms • no metabolism, no linkage with lower scale levels Cottbus, 10. 3. 2008

  17. structural models – drawbacks: • no (or very sparse) taking into acount of the functional aspects of organisms • no metabolism, no linkage with lower scale levels combination of model types Cottbus, 10. 3. 2008

  18. (c) Functional-structural plant models, FSPM Idea: distribution of the processes to the modules

  19. (c) Functional-structural plant models, FSPM Idea: distribution of the processes to the modules Tool: object-oriented programming example of ALMIS (Eschenbach 2000)

  20. (c) Functional-structural plant models, FSPM Idea: distribution of the processes to the modules Tool: object-oriented programming example of ALMIS (Eschenbach 2000)

  21. FSPM example LIGNUM (Perttunen et al. 1996, 1998, Dzierzon & K. 2002; Sievänen et al. 2006)

  22. Drawbacks of ad hoc FSPMs from the last years: • isolated solutions, often strongly specialized Cottbus, 10. 3. 2008

  23. Drawbacks of ad hoc FSPMs from the last years: • isolated solutions, often strongly specialized • large, complex source code, • containing technical details mixed with • fundamental features of the model Cottbus, 10. 3. 2008

  24. Drawbacks of ad hoc FSPMs from the last years: • isolated solutions, often strongly specialized • large, complex source code, • containing technical details mixed with • fundamental features of the model • low compatibility of the models with each other Cottbus, 10. 3. 2008

  25. Drawbacks of ad hoc FSPMs from the last years: • isolated solutions, often strongly specialized • large, complex source code, • containing technical details mixed with • fundamental features of the model • low compatibility of the models with each other a further challenge: • complexity of the tool (for the user) has to be reduced Cottbus, 10. 3. 2008

  26. traditional, commonly-used programming languages obviously not optimal for the purpose Cottbus, 10. 3. 2008

  27. formal basis for tools in ecological informatics? • grammars Cottbus, 10. 3. 2008

  28. formal basis for tools in ecological informatics? • grammars Eric Mjolsness, Univ. of California 2006: "Future multiscale models must be able to integrate all the major different types of dynamical systems models, ... These goals are achieved by the modelling framework of... grammars." Cottbus, 10. 3. 2008

  29. 2. Relational Growth Grammars (RGG) as a generic tool on a formal level point from where to start: L systems (parallel string rewriting) Cottbus, 10. 3. 2008

  30. Limitations of L-systems: • in L-systems, only 2 possible relations between objects: "direct successor" und "branching" Cottbus, 10. 3. 2008

  31. Limitations of L-systems: • in L-systems, only 2 possible relations between objects: "direct successor" und "branching" • multiscaled models are not supported Cottbus, 10. 3. 2008

  32. Limitations of L-systems: • in L-systems, only 2 possible relations between objects: "direct successor" und "branching" • multiscaled models are not supported • object-oriented programming is not supported (only symbols, resp. "modules" = parameterized symbols, no objects, no classes) Cottbus, 10. 3. 2008

  33. Limitations of L-systems: • in L-systems, only 2 possible relations between objects: "direct successor" und "branching" • multiscaled models are not supported • object-oriented programming is not supported (only symbols, resp. "modules" = parameterized symbols, no objects, no classes) • structures must be serialized to strings Cottbus, 10. 3. 2008

  34. Limitations of L-systems: • in L-systems, only 2 possible relations between objects: "direct successor" und "branching" • multiscaled models are not supported • object-oriented programming is not supported (only symbols, resp. "modules" = parameterized symbols, no objects, no classes) • structures must be serialized to strings  transgression to graph grammars

  35. "Relational Growth Grammars" (RGG) as generic tool on a formal level = graph grammars with parallel application Cottbus, 10. 3. 2008

  36. "Relational Growth Grammars" (RGG) • as generic tool on a formal level • = graph grammars with parallel application • • graph model: • with node attributes and types (type hierarchy • for inheritance) • with edge labels (finitely many) • no multiple edges with the same label Cottbus, 10. 3. 2008

  37. Nodes:  correspond to the symbols in L-systems Cottbus, 10. 3. 2008

  38. Nodes:  correspond to the symbols in L-systems  simultaneously objects sensu OOP Cottbus, 10. 3. 2008

  39. Nodes:  correspond to the symbols in L-systems  simultaneously objects sensu OOP  e.g., plant organs, geometric transformations Cottbus, 10. 3. 2008

  40. Edges: their labels can represent different sorts of relations: • is successor of • contains • bears as a lateral shoot • reacts with • encodes (genetically) • is mating with • (...)  also possible: representation of multiscaled structures Cottbus, 10. 3. 2008

  41. multiscaled structures (different geometric levels of resolution in one model) relation of refinement (AMAPmod software description, CIRAD Montpellier, 1998)

  42. multiscaled structures (different geometric levels of resolution in one model) relation of refinement (AMAPmod software description, CIRAD Montpellier, 1998) in computer graphics: "Level of Detail"

  43. RGG replacement mechanism left-hand side of rule right-hand side of rule ●embedding model: Single-Pushout approach from algebraic graph grammar theory, extended by so-called connection transformations ● right-hand sides of rules are dynamically generated Cottbus, 10. 3. 2008

  44. an RGG rule and its application in graphical form: rule: application: Cottbus, 10. 3. 2008

  45. an RGG rule and its application in graphical form: rule: application: rule in text form:i -b-> j -a-> k -a-> i ==> j Cottbus, 10. 3. 2008

  46. implicit use of "connection edges" for the desired embedding: a:A ==>> a C (SPO rule) B ==> D E (rules of L-system type) C ==> A original graph: A B C Cottbus, 10. 3. 2008

  47. implicit use of "connection edges" for the desired embedding: a:A ==>> a C (SPO rule) B ==> D E (rules of L-system type) C ==> A A B C connection edges (auxiliary edges) D E A Cottbus, 10. 3. 2008

  48. implicit use of "connection edges" for the desired embedding: a:A ==>> a C (SPO rule) B ==> D E (rules of L-system type) C ==> A A B C a: D E A Cottbus, 10. 3. 2008

  49. implicit use of "connection edges" for the desired embedding: a:A ==>> a C (SPO rule) B ==> D E (rules of L-system type) C ==> A A D E A a: C Cottbus, 10. 3. 2008

  50. Advantages:  L-systems as a special case Strings correspond to special graphs Cottbus, 10. 3. 2008

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