Purpose The purpose of my research project is to create a simulation of a many-species, non-static, many-variable ecosystem According to user preferences,

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Presentation transcript:

Purpose The purpose of my research project is to create a simulation of a many-species, non-static, many-variable ecosystem According to user preferences, many desired ecosystem simulations will be able to be run. In my case, I am focusing limiting the species to the dinosaurs of the late Cretaceous era

Subject / Goals The scope of my project will include hypothetical situations, which will be applicable to real-life, and possibly a real-world model Based on known facts of the dinosaurs, the user will be able to input unknown or hypothetical facts about dinosaurs and thus create a possible simulation of what could have happened on our Earth in the Cretaceous era

Overview Producer / Predator / Prey dinosaur ecosystem based on the late Cretaceous era with chance factors Unique species Consequence algorithm for dinosaur conflicts Trait accumulation Reproduction algorithm for mutations and creations of new species Natural disasters Eggs

Expected Results I will validate success by the accuracy as represented by the common behavior of real world ecosystems For example, if there are many carnivores preying on a few herbivores, the expected results in sequence would be: 1 – Herbivores are near extinction / are extinct. 2 – Carnivores begin to die out. 3 – Grass regrows fully.

Other Research Cellular Automata Model of Macroevolution: the constant evolution of a biomass of a multi-species system A Jump-Growth Model for Predator-Prey Dynamics: derivation and application to marine ecosystems: evolution to catch prey, equation to calculate populations Predator-Prey Model: linear rate (Lotka-Volterra), group immunity (Kermack-McKendrick), constant uptake (Jacob-Monod), carrying maximum capacity (Logistic), self-predation (Ricker's)

Other Research Biomechanics of Running Indicates Endothermy in Bipedal Dinosaurs: energy-size ratio, warm-blooded / endothermic dinosaurs Fossil Record of Predation in Dinosaurs: predatory features, consumption records, chemical analyses What killed the Dinosaurs? A Great Mystery: exploring the K-T extinction theory and the surrounding events

Usage Load the program Use sliders Toggle on/off desired functions Hit 'Setup' 'Step' for 1 iteration, 'Go' for continuous (adjusted by speed bar at the top)

Procedures / Methods Using NetLogo Accomplishing by building top-down, building simple, then advancing to more advanced functions A complicated simulated system with many variables for the user to control BehaviorSpace for data storage

Timeline Q1 : Basics – Predator-prey, herbivore-producer, basic predation, modeling Q2 : Dinosaur focus – narrowed late Cretaceous, predation range, additional 2 species, reproduction algorithm, prey selection algorithm, movement algorithm Q3 : Another producer I have implemented more than one producer, water spots, geological dead zones, natural disasters, and eggs.

Project Testing / Problems Project testing simply consists of running the program and comparing it to the expected results, and finding inconsistencies with real-life dinosaur simulation possibilities and expected ecosystem results The NetLogo program runs almost exclusively to working programs – if it's incomplete, it can not run, instead giving an error Currently, the only existing error is that I can not get each egg to hatch into specifically different dinosaurs without adding an additional and cheap variable. In order to do it using a general algorithm, I simply need to create uniquely colored eggs than have some sort of color boolean check if it is a certain color, and hatch it.

Algorithms Grass regrowth Generic consumption Conflict sequence Predation range Reproduction Prey selection Natural disaster Eggs Unique encounters Extinction Time Growth (working)

Hypothesis Due to the harsh environment of the dinosaur ages, species fluctuations as the result of these powerful beasts' conflicts can cause an imbalance in the ecosystem. Learning from the results given the specific parameters, based on the populations involved

Results 1 Predator / High Energy Gain / High Reproduction Invasive Species Effect Drought Effect Flood Effect Earthquake Overgrowth Effect Over Predation