Summary: | For rare species to be saved for a self-sustaining ecology, it is crucial to understand how their populations work, especially in important locations like their breeding grounds. This study digs deep into the lives of the Whooping Cranes (Grus Americana) that only breed in the environment of Wood Buffalo National Park (WBNP) located in NWT/AB and are highly endangered and on the verge of extinction. Using a novel modelling technique called Agent-Based Modelling (ABM), this study gives a detailed look at how individual behaviours, relationships between species, and their environment all affect the population dynamics of endangered cranes. This research, which can be located at the intersection of ecology and computer modelling, employs actual population data of whooping cranes that are obtained from Canadian Wildlife Service (CWS), and ABM-ing approach to untangle the complex web of factors that affect the fate of whooping crane populations. This includes the biological features of whooping cranes, and the effect of climate change on reproduction success in Wood Buffalo National Park. Through rigorous ABM simulations, this approach not only catches the complexity of these correlations, but it also provides a flexible tool for simulating and testing different scenarios, which makes it possible to look at what might happen with different conservation tactics. ABM has given us some early insights that show how important it is for whooping cranes to understand breeding dynamics in Wood Buffalo National Park. These results show where conservation efforts should be directed and how important it is to protect and fix up these areas. Also, the dynamic nature of ABM shows how biological effects ripple through the ecosystem, giving a full picture of how various parts of this complex environment depend on each other. In short, this examination not only shows how the threatened whooping crane's population changes in the unique breeding ground in Wood Buffalo National Park, but it also shows how agent-based modelling in ...
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