Solving T(n) = 2T(n/2) + log n with the recurrence tree method
The non-recursive term of the recurrence relation is the work to merge solutions of subproblems. The level $k$ of your (binary) recurrence tree contains $2^k$ subproblems with size $\frac {n}{2^k}$, so you need at first to find the total work on the level $k$ and then to summarize this work over all the tree levels. 

For example, if the work is constant $C$, then the total work on the level $k$ will be $2^k \cdot C$, and the total time $T(n)$ will be given by the following sum:

$$T(n) = \sum_{k=1}^{\log_2{n}}2^k C = C(2^{\log_2{n}+1}-2) = \Theta(n)$$

However, if the work logarithmically grows with the problem size you'll need to accurately compute the solution. The series would be like the following:

$$T(n)=\log_2{n}+\underbrace{2\log_2(\frac {n} {2})+4\log_2(\frac {n} {4})+8\log_2(\frac {n} {8}) + ....}_{\log_2{n} \text{ times}}$$

It'll be a quite complex sum:

$$T(n)=\log_2{n}+\sum_{k=1}^{\log_2{n}}2^k \log_2(\frac {n} {2^k})$$

I'll temporarily denote $m=\log_2{n}$ and simplify the summation above:

$$\sum_{k=1}^{m}2^k \log_2(\frac {n} {2^k})=\\=\sum_{k=1}^{m}2^k(\log_2{n}-k)=\\=\log_2{n}\sum_{k=1}^{m}2^k-\sum_{k=1}^{m}k2^k=\\=\log_2{n}(2^{m+1}-2)-(m2^{m+1}-2^{m+1}+2)$$

Here I used a formula for the $\sum_{k=1}^{m}k2^k$ sum from the Wolfram|Alpha online symbolic algebra calculator. Then we need to replace $m$ back by $\log_2{n}$: 

$$T(n)=\log_2{n}+2n\log_2{n}-2\log_2{n}-2n\log_2{n}+2n-2$$
$$=2n-\log_2{n}-2=\Theta(n)$$

Q.E.D.