dynamic range (DR) should be a factor of the signal to noise ratio, fill factor of the sensor, and signal processing, rather than the bit depth...
as I explained somewhere else in the forum, imagine you have a S$1 and US$1... the US$1 will have more monetary value than the S$1 even though the numerical value is the same (i.e. both are 1)... now imagine the S$1 is divided into 10S¢ coins... you would have 10x10S¢ coins... but if you divided into 1S¢ coins you would have 100x1S¢ coins... if you do the same for US$1, you would have 10x10US¢ and 100x1US¢ coins...
now to tie it all together... DR is like how wide a range of brightness values you can record... a wider dynamic range would be able to record a greater range of values from dark to bright, and vice versa... signal to noise ratio of the sensor affects DR by determining what is the darkest value that may be recorded, past which the sensor cannot determine if what is captured is noise or part of the image... light fill factor of the sensor determines what's the brightest values that may be recorded, past which only perfect whiteness will be recorded ... and signal processing determines at what values the camera will actually stop the processing for recording brightest or darkest values, as well as what values to assign what levels of brightness... as can be seen here, cannot really tell the DR of a camera by looking at any one value, and certainly not from the specs given by manufacturers... only real way for the consumer is to try the camera out, or believe what the manufacturers' marketing and PR materials tell you...
taking the $1 analogy, the DR can be said to be like the $1, where there are $1 with more value (US$1) and $1 with less value (S$1)... bit depth (i.e. how many bits, whether 8bit, 12bit, 14bit, etc.) on the other hand is like how finely you divide the $1... so you can divide your $1 into 10¢ or 1¢... whether its US$1 or S$1, in the first form of division, you would still get 10 coins, and in the second form of division you would still get 100 coins, just that each of the coins in their respective currency will still have different values as well... so high bit depth is like dividing the $1 into coins of smaller value, where you would get a larger number of coins and the value of $1 is divided more finely, whereas a low bit depth is like dividing the $1 value with larger coins and the $1 is divided less finely... but the absolute value of the $1, for the case of currency, or the DR, in the case of an image, is still the same whether its divided finely or not...
these explanations are of course gross simplifications...
sorry for this massive OT... ;p