How plants changed the world: Using qualitative reasoning to explain plant macroevolution's effect on the long-term carbon cycle
2013
Kansou, Kamal | Nuttle, Tim | Farnsworth, Katie | Bredeweg, Bert | Unité de recherche sur les Biopolymères, Interactions Assemblages (BIA) ; Institut National de la Recherche Agronomique (INRA) | Indiana University ; Indiana University [Bloomington] ; Indiana University System-Indiana University System | Civil & Environm Consultants Inc ; Partenaires INRAE | Vrije Universiteit Amsterdam [Amsterdam] (VU) | EC [231526]; IUP Academic Excellence and Innovation award
International audience
显示更多 [+] 显示较少 [-]英语. We present a qualitative reasoning model of how plant colonization of land during the mid Paleozoic era (450-300 million years ago) altered the long-term carbon cycle resulting in a dramatic decrease in global atmospheric carbon dioxide levels. This model is aimed at facilitating learning and communication about how interactions between biological and geological processes drove system behavior. The model is developed in three submodels of the main system components, namely how competition for limited land habitat drove natural selection for increasing adaptations to life on land; how these adaptations resulted in increased formation of organic-rich sedimentary rocks (coal); and how these adaptations altered weathering of calcium and magnesium silicate rocks, resulting in increased deposition of inorganic carbonates in oceans. These separate submodels are then assembled to derive the full dynamic model of plant macroevolution, colonization of land, and plummeting carbon dioxide levels that occurred during the mid Paleozoic. The qualitative reasoning framework supports explicit representation of causal feedbacks as with previously developed systems analysis models - but also supports simulation of system dynamics arising from the configuration of entities in the system. The ability of qualitative reasoning to provide causal accounts (explanations) of why certain phenomena occurred and when, is a powerful advantage over numerical simulation such as the complex GEOCARB models, where explanation must be left to interpretation by experts. (C) 2013 Elsevier B.V. All rights reserved.
显示更多 [+] 显示较少 [-]