Insight Maker Introduction and Demonstration

Summary

The video introduces a Population Viability Analysis (PVA) model to simulate the extinction of a squirrel population due to death alone. Using a binomial distribution, the model accounts for randomness in the population's survival, showing how uncertain outcomes, such as the year of extinction, can vary even under similar conditions. The speaker demonstrates the sensitivity testing tool, which runs multiple simulations to plot diverse extinction outcomes. This process highlights the unpredictability in ecological modeling and emphasizes the importance of understanding uncertainty when forecasting population trends.

Takeaways

• 😀 The speaker demonstrates the use of a **deterministic model** to simulate squirrel population dynamics, focusing on how variables like birth and death rates affect population growth.
• 😀 A **binomial distribution** is introduced to simulate the random nature of death in the squirrel population, akin to flipping coins to represent the chance of death for each squirrel.
• 😀 The **death rate** is modeled by flipping a number of virtual coins equal to the squirrel population, with the probability of heads representing the chance of a squirrel dying.
• 😀 Randomness is incorporated into the model, making the exact time of extinction uncertain, even though the population is destined to go extinct eventually.
• 😀 The speaker demonstrates how starting with a small population size increases randomness, leading to earlier extinction in some simulations.
• 😀 The **sensitivity testing tool** allows running the model multiple times (e.g., 100 times) to observe different outcomes and quantify the uncertainty in extinction timing.
• 😀 The model shows that the squirrel population will go extinct, but the exact year of extinction can vary significantly based on random events in each simulation.
• 😀 The use of the sensitivity tool enables the visualization of all 100 simulation runs, showing that some populations go extinct quickly, while others persist longer.
• 😀 The **sensitivity testing** highlights the **uncertainty** of predicting exact outcomes in population modeling due to the inherent randomness of birth and death rates.
• 😀 The speaker emphasizes that even with a lack of births, the population's eventual extinction is inevitable, but the timing remains uncertain.
• 😀 The demonstration concludes with an overview of **population viability analysis (PVA)**, where models like these are useful to understand the uncertain future of populations.

Q & A

What is Population Viability Analysis (PVA)?

Population Viability Analysis (PVA) is a tool used to predict the likelihood of a population's survival over time, considering factors such as birth rates, death rates, and environmental variability.

How is randomness incorporated into the squirrel population model?

Randomness is introduced through a binomial distribution, which simulates 'flipping coins' for each squirrel. Each coin flip has a probability of landing heads, representing a squirrel's death based on a specified death rate.

Why is the binomial distribution used in this model?

The binomial distribution is used because it allows for simulating random events with a fixed probability, such as the death of squirrels, across a set number of individuals (squirrels in this case).

How does the population start and what happens to it in the model?

The population starts with a set number of squirrels (e.g., 10) and declines over time due to deaths. Because of the randomness introduced by the model, the population's path to extinction varies in different simulations.

What is the purpose of using a sensitivity testing tool in this model?

The sensitivity testing tool allows the model to run multiple simulations (e.g., 100 times) to observe the variability in extinction times. This highlights the uncertainty about when the population will go extinct, despite knowing it will eventually occur.

What kind of variability does the sensitivity testing tool reveal?

The sensitivity testing tool reveals that the population may go extinct at different times across simulations. For example, in one simulation, extinction might occur in year 7, while in another, it could be as late as year 38.

What does the green line in the simulation represent?

The green line represents the squirrel population, showing how it changes over time. It visually demonstrates the decline in population until extinction occurs.

Why is there uncertainty in the timing of the population's extinction?

Uncertainty arises because the model incorporates random events (squirrel deaths), which means the exact timing of extinction depends on chance. This randomness leads to different outcomes in each simulation.

How does the model demonstrate the impact of no birthrate on population survival?

The model shows that without a birthrate, the population will eventually go extinct due to the accumulation of deaths over time. However, the exact timing of extinction is uncertain due to the randomness in death events.

What is the significance of using multiple simulations in the model?

Running multiple simulations allows for a more robust analysis of the potential outcomes and highlights the variability in results. It provides insight into the range of possible extinction times, making the model more reflective of real-world uncertainty.