The statement
Statement 1: The square root is not a linear transformation.
is not generally true, at least as it stands.
According to the most often applied definition (see, e.g., Wikipedia), a linear transformation $f : V \to W$ is a mapping between two vector spaces/ modules $V$ and $W$ over the same field/ ring.
The difficulty is to acknowledge that the operations on $V$ and $W$ can well be different from usual addition and usual multiplication, even if the symbols $+$ and $\cdot$ are often used to denote vectos addition and and scalar multiplication of an abstract vector space. The terms of the two operation are themselves suggestive, but misleading. Indeed, when the vector space under consideration is the concrete vector space $\mathbb{R}$, then vector addition and scalar multiplication agree with usual addition and usual multiplication; but there are numerous examples in which this is not the case. An important and simple example is the vector space of the positive-real numbers, $\mathbb{R}_{>0}$, in which multiplication and exponentiation take on the role of vector addition and scalar multiplication.
Now consider the OP's square-root function $f$. The domain of $f$ cannot be $\mathbb{R}$, because the square root is not defined for negative values (let us leave aside the complex-valued case). Therefore, it is questionable if the operations of $\mathbb{R}$ are, afer all, validly used to proof that Statement 1 is true. It may well be argued that the proofs of Statement 1 are flawed, because the requirements of the definition of a liear map are not met. The appendage in the OP's question, $\sqrt{1 + x^2} \neq 1 + x$, is actually irrelevant for this matter.
In fact, one can easily prove, meeting all requirements of the definition of a linear map, the converse of Statement 1:
Proposition 1: The map $f : \mathbb{R}_{>0} \to \mathbb{R}_{>0}, \, x \mapsto \sqrt{x}$ is a linear transformation.
Proof:
Let $x,y \in \mathbb{R}_{>0}$, and let $\lambda \in \mathbb{R}$. Then
$$
\begin{array}{rclr}
f(x \cdot y) =& \sqrt{x \cdot y} = \sqrt{x} \cdot \sqrt{y} &= f(x) \cdot f(y) & \text{(preservation of vector addition)} \\
f(x^\lambda) =& \sqrt{x^\lambda} = \left( \sqrt{x} \right)^\lambda &= f^\lambda(x) & \text{(preservation of scalar multiplication)}
\end{array}
$$
$$\tag*{$\square$}$$