The apparent decline of the salmon in the Columbia river system is one of the most complex environmental problems we have.
However, this problem has been oversimplified by the media and others to one single root cause, namely the construction of hydroelectric dams on the Columbia river system.
Today we wish to access of this simplification is valid. The next homework assignment given will allow you to explore this issue in more depth as well. For today we want to examine some of the broader issues and look at the actual data which is available.
The Salmon controversy is an excellent example of arguments made largely on belief, instead of knowledge that is supported by the actual data .
Factors Causing Salmon Decline:
Broad Brush Factors:
More Detailed Factors in relation to Above:
Let's look at some data. Most of this data comes from fish counts done at Bonneville Dam starting in 1938 (again the next homework assignment will have you make use of this data):
Blue line represents growth of nonharvested fish in the Columbia River system. The implication is that competition for food/nutrients is increasing rapidly. 
Its getting warmer earlier in the season with time in the Columbia river. Is this cause local (e.g. dams/ag) or global (e.g. Global Warming) 
Graph shows harvesting by Tribal communities with protected fishing rights. Some degree of "over harvesting" is apparent. 

Graph shows total salmon catch off the coast of North America (including Alaska). 
Decline of InRiver catches which is
frequently used as the "best" indicator for overall salmon decline
in the Columbia River System: 
Implication is that increases in ocean catch are directly responsible for decreases of inriver catches also shown. 
That is, if the true salmon count is down by a factor of say 100, relative to what it was 100 years ago, then our salmon efficiency in harvesting would have to increase by at least a factor of 100 to make up the difference. I think this is unlikely.
This is the raw salmon count data at Boneville Dam that we will inspect more closely below. Evidence of quasicylical behavior is apparent. 
Some relevant WWW resources for the above:
Using the fish count data, can we determine if there is a significant decline? Yes, we can determine this from the statistical tools we have been talking about.
Comparing Two Sample Means  Find the difference of the two sample means in units of sample mean errors. This works as follows:
Difference in terms of signifance is:
Simple Approximation:
The actual salmon count data:
This distribution, defined by 44 points, has a mean of 358,000 salmon with a dispersion of 82,000 salmon. The error in the mean is 12,000 (82000/(square root of 44))
Points to note about the distribution:
Here is the distribution of the data with the last 5 years subtracted out, so there are 39 years worth of data:
This distribution, defined by 39 points, has a mean of 368,000 salmon with a dispersion of 81,000 salmon and a mean error of 13,000.
Note: The dispersion for the 39 year sample and the 44 year sample are similar this indicates that we have enough data to accurately determine the dispersion.
Over the last 5 years, the data are defined by an average of 278,000 salmon with a dispersion of 33,000 and a mean error of 15,000 = (33,000/(sqrt of 5)). Does this data show a significant decline of salmon?
Since the mean errors are similar we can use (M1M2)/1.5E1 for an approximation: