The function that describes the deer population in the state park is given by:

$d(x) = 2500(1.043)^x$

Where:

• $d(x)$ represents the population of deer at time $x$ (in years).
• $x$ is the number of years since tracking began.
• The number 2500 is a coefficient that gives us the initial population when $x = 0$.

To find how many deer were in the park when tracking began (i.e., at $x = 0$), substitute $x = 0$ into the equation:

$d(0) = 2500(1.043)^0$

Since any number raised to the power of 0 equals 1:

$d(0) = 2500 \times 1 = 2500$

So, the deer population when tracking began was 2500.

Answer: 2500

---

Would you like more details on how this population model works or have any further questions? Here are some related questions for you:

1. What does the base $1.043$ represent in the context of this model?
2. How would the population change if the base was 1.05 instead of 1.043?
3. How can this model be used to predict the population of deer in the future?
4. How would you interpret the value of $d(x)$ when $x = 5$?
5. What type of growth does this equation represent: linear, exponential, or something else?

Tip: When working with exponential growth models, the base of the exponent shows how much the population increases (or decreases) per unit time.