ecological modeling and decision support systems
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Ecological Modeling and Decision Support Systems P. Struss and O. Dressler WS 13/14 WS 13/14 EMDS 1 - 1 Model-Based Systems & Qualitative Reasoning Group of the Technical University of Munich Ecological Modeling and Decision Support


  1. Ecological Modeling and Decision Support Systems P. Struss and O. Dressler WS 13/14 WS 13/14 EMDS 1 - 1 Model-Based Systems & Qualitative Reasoning Group of the Technical University of Munich

  2. Ecological Modeling and Decision Support Systems 1 The Topic  Definition of ecology  Concepts in ecology  Environmental problems  The role of IT  The special challenges for IT  Decision support  The focus of the course Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 2 Group of the Technical University of Munich

  3. „Eco - Informatics“?  Simply an application of computer science to a particular domain?  Like bio- informatics, medicine informatics, …  Same methods and techniques  E.g. DB technology, simulation, image analysis, …  Specific challenges for IT in ecology?   What is ecology?   What could be supported by IT? Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 3 Group of the Technical University of Munich

  4. Ecological Modeling and Decision Support Systems Example: Impact of Introduction of Trout in New Zealand Model-Based Systems & Qualitative Reasoning - 4 WS 13/14 EMDS 1 Group of the Technical University of Munich

  5. Example: Impact of Introduction of Trout in New Zealand  Trout introduced to NZ rivers (1867)  For fishing  Compete with native fish (Galaxias)  Both feed on invertebrates  (sections of) rivers – No fish – Trout only – Galaxia only – Both species  So what?  Impact?  Field study Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 5 Group of the Technical University of Munich

  6. Counting Visible Invertebrates  Difference  Different ways of locating prey – hiding/visibility – Trout: visually – Daytime - night – Galaxias: mechanically 12 12 16 16 Day Day Nigh ght 12 12 Nesameletus visible Deleatidium visible 8 8 4 4 0 0 Galaxias stream Trout stream No fish Galaxias Trout Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 6 Group of the Technical University of Munich

  7. Abundance of the Fish Species  Trout migrate upstream  Prevented by waterfalls   correlation with elevation VARIABLES NUMBER OF ELEVATION % OF THE BED NUMBER WATERFALLS (m ABOVE COMPOSED OF SITE TYPE OF SITES DOWNSTREAM SEA LEVEL) PEBBLES Brown trout only 71 0.42 (0.05) 324 (28) 18.9 (2.1) Galaxias only 64 12.3 (2.05) 567 (29) 22.1 (2.8) No fish 54 4.37 (0.64) 339 (31) 15.8 (2.3) Trout + Galaxias 9 0.0 (0) 481 (53) 46.7 (8.5) Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 7 Group of the Technical University of Munich

  8. Impact on Invertebrates and Algae  Compared to Galaxias  Trout: – reduced population of invertebrates – Increased biomass of algae 2 4 Invertebrate biomass (g m 2 ) Algal biomass (µg cm 2 ) 3 1 2 1 0 0 N G T N G T Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 8 Group of the Technical University of Munich

  9. Biomass – Production and Demand AFDM: Ash-free Dry Mass Demand Production 350 14 2,5 Production/demand (g AFDM -1 m -2 ) 300 12 2 250 10 1,5 8 200 150 6 1 4 100 0,5 2 50 0 0 0 Galaxias Trout Galaxias Trout Galaxias Trout Invertebrates Algae Fish Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 9 Group of the Technical University of Munich

  10. Further Impact?  Potential continuation of the causal chain  Algae feed on nitrate, ammonium, sulfate   Reduced concentration of nitrate, ammonium, sulfate downstream   … …  Boundaries of the analysis, the model, … Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 10 Group of the Technical University of Munich

  11. Ecological Modeling and Decision Support Systems Ecology: Definitions and Basic Concepts Model-Based Systems & Qualitative Reasoning - 11 WS 13/14 EMDS 1 Group of the Technical University of Munich

  12. Ecology – (One) Definition “The scientific study of the distribution and abundance of organisms and the interactions that determine distribution and abundance” (Townsend et al. 08) Interactions?  at various levels – Individuals – Species – Physical environment Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 12 Group of the Technical University of Munich

  13. Levels of Interaction – Individual Individual Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 13 Group of the Technical University of Munich

  14. Levels of Interaction – Population Population Individual Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 14 Group of the Technical University of Munich

  15. Levels of Interaction – Community Community Population Individual Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 15 Group of the Technical University of Munich

  16. Levels of Interaction – Ecosystem Ecosystem Community Population Individual Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 16 Group of the Technical University of Munich

  17. Different Spatial Scales  Global climate change  ocean currents  fish populations  …  Plant population in a rain forest  …  Inhabitants of water-filled tree holes  …  Bacteria in termites’ guts Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 17 Group of the Technical University of Munich

  18. Different Temporal Scales  Ecological succession since the Ice Age  …  Migration and mating cycle of turtles  …  Organisms in decomposition of sheep dung Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 18 Group of the Technical University of Munich

  19. Different Sciences and Knowledge Sources  Biology  Chemistry  Physics  Geophysics  Hydrology  … Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 19 Group of the Technical University of Munich

  20. For Instance, Trout Field Study – Aspects  Levels to be considered?  Spatial aspects?  Temporal aspects?  Disciplines involved? Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 20 Group of the Technical University of Munich

  21. Ecological Modeling and Decision Support Systems Ecology: Tasks and Goals Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 21 Group of the Technical University of Munich

  22. Ecology – Goals? “The scientific study of the distribution and abundance of organisms and the interactions that determine distribution and abundance” (Townsend et al. 08)  Description …  … only? Describe Explain  Understanding …  … only?  Prediction  … only? Predict Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 22 Group of the Technical University of Munich

  23. Understand in Order to Influence Motivation:  Limit bad impact of human activity  Secure continued exploitation  “Environmental problems” Describe Explain Ref.: Manage, Townsend et al., Predict Essentials of Ecology Control Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 23 Group of the Technical University of Munich

  24. Ecological Modeling and Decision Support Systems Example: Degradation of Mangroves in India Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 24 Group of the Technical University of Munich

  25. Optimism - „We will preserve local flora and fauna“  „In this area the Forest Department of the Pichavaram Mangroves has started management activities in 1995 in order to preserve the local flora and fauna.“ Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 25 Group of the Technical University of Munich

  26. Meanwhile, Upstream ... Dams in Cauvery River Reduction of Sediments in the River Less Deposition in River Delta Trough-shaped Basin Stagnant Water Increased Salinity Degradation of Mangroves Reduced Shelter Against Cyclones, Tsunamis Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 26 Group of the Technical University of Munich

  27. “Side - effects” ... Increased Salinity Evaporation Degradation of Mangroves Trough-shaped Basin Stagnant Water Cyclones Less Deposition in River Delta Dams in Cauvery River Reduction of Sediments “Environment” in the River Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 27 Group of the Technical University of Munich

  28. Ecological Modeling and Decision Support Systems Humans and “Environment” Model-Based Systems & Qualitative Reasoning - 28 WS 13/14 EMDS 1 Group of the Technical University of Munich

  29. “Environment”??...  Limit bad impact of human activity  Secure continued exploitation  “Environmental problems”   Problems of human activity, economy, health, …  Welt  Umwelt!!  Anthropocentric perspective “Environment” Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 29 Group of the Technical University of Munich

  30. Anthropocentric Perspective Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 30 Group of the Technical University of Munich

  31. “Side - effects” ... Increased Salinity Evaporation Degradation of Mangroves Trough-shaped Basin Stagnant Water Cyclones Less Deposition in River Delta Dams in Cauvery River Reduction of Sediments in the River Model-Based Systems & Qualitative Reasoning WS 13/14 EMDS 1 - 31 Group of the Technical University of Munich

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