Estimating statistical power to evaluate ongoing waterfowl population monitoring

The probability of failing to detect a trend when 1 exists has been conside red only rarely in the interpretation of monitoring studies. Retrospective power analysis accomplishes this assessment. me apply retrospective power a nalysis to evaluate both population trends and survey design in the waterfo wl surveys conducted by the Canadian Wildlife Service and others around Ris ke Creek, British Columbia. Eleven of 18 species showed long-term (17 yr) a nd short-term (10 yr) trends. For the remaining 7 species, the long-term an alysis had sufficient power (0.8) to have detected at least a 5% annual cha nge, had 1 existed, which supported the conclusion that little change occur red. However, statistical power and detectable effects varied considerably among species, with a range of 3-14 years of data needed to be able to dete ct a 5% annual trend. When we used the shorter-term dataset, power was redu ced below acceptable levels for 4 of the 7 species failing to show a trend. It would be a mistake to conclude that the numbers of these 4 species were not changing. Statistical power was highest for the species for which the surveys were originally designed, Barrow's goldeneye (Bucephala islandica) and mallards (Anas platyrhynchos), which had narrow confidence intervals an d relatively small minimum detectable trends. In contrast, blue-winged teal (Anas discors), gadwall (Anas strepera), green-winged teal (Anas crecca), northern pintail (Anas acute), and northern shoveler (Anas clypeata) had re latively large minimum detectable trends and nide confidence intervals. Muc h of the power of these surveys was due to repeated surveying within season s. For most species, power increased substantially by including up to 4 sur veys as replicate observations within a year, but power increased little wh en data from a fifth or sixth survey were included.