​Predator-prey models are the building masses of the bio-and environments as bio masses are become out of their asset masses. Species contend, advance and scatter essentially to look for assets to support their battle for their very presence. This model is designed to represent the moose and wolf population on Isle Royal. The variables include moose population, wolf population, moose birth rate, wolf birth rate, moose death proportionality constant, and wolf death proportionality constant. This model was adapted from https://insightmaker.com/insight/3A0dqQnXXh8zxWJtkwwAH9/Lotka-Volterra-Model-Prey-Predator-Simulation.

 Looking at Lotka-Volterra Model:

The well known Italian mathematician Vito Volterra proposed a differential condition model to clarify the watched increment in predator fish in the Adriatic Sea during World War I. Simultaneously in the United States, the conditions contemplated by Volterra were determined freely by Alfred Lotka (1925) to portray a theoretical synthetic response wherein the concoction fixations waver. The Lotka-Volterra model is the least complex model of predator-prey communications. It depends on direct per capita development rates, which are composed as f=b−py and g=rx−d. 

A detailed explanation of the parameters:

• The parameter b is the development rate of species x (the prey) without communication with species y (the predators). Prey numbers are reduced by these collaborations: The per capita development rate diminishes (here directly) with expanding y, conceivably getting to be negative. 
• The parameter p estimates the effect of predation on x˙/x. 
• The parameter d is the death rate of species y without connection with species x. 
• The term rx means the net rate of development of the predator population in light of the size of the prey population.

Reference:

http://www.scholarpedia.org/article/Predator-prey_model

https://insightmaker.com/insight/3A0dqQnXXh8zxWJtkwwAH9/Lotka-Volterra-Model-Prey-Predator-Simulation

Use the sliders to experiment with the initial amount of non-renewable resources to see how these affect the simulation. Does increasing the amount of non-renewable resources (which could occur through the development of better exploration technologies) improve our future? Also, experiment with the start date of a low birth-rate, environmentally focused policy.