Bill Pulliam is to be congratulated for sending his Breeding Bird Survey (BBS) graphs to tn-bird. It is not often that we get to consider science on tn-bird and I for one would like to see more of it. Also impressive was the overall look of the presentation. All in all a fine contribution, well worth the effort. I have spent a few days reading BBS materials and research acticles and these are some of my more general thoughts. First, BBS samples are essentially "convenient" samples and the observations are not randomly distributed. Those responsible for the BBS say that in targeted habitats suitable roads on which roadside observations take place were chosen randomly. In other words, roadside observations in selected habitats are privileged. Hypothetically, compared to other places some birds may increase, others decrease in these putatively dynamic roadside environments. Those who do spatial analyses, geographers, economists, sociologists, epidemiologists, and medical researchers, know that convenient samples and others that are not randomly distributed are not without serious problems. For example, and having used these methods quite a bit in the past, I know that different spatial units often produce markedly different results. What this means is that if we had another data set using different methods with which to compare the BBS data, it is likely that we would find different results for at least some species. Scientists who do not use comparable data sets may not fully appreciate the degree to which results can differ. That is what Roger Applegate is saying. Another way of looking at this is that if the BBS had a larger sample, and with convenient samples that is quite important, the results would have been more convincing. Second, this is not, or should not be, the end of the story. Knowing that the data are flawed should be the beginning of our investigation. Note that flawed data may not produce results that are systematically biased. If possible the next step is to determine if there is bias. Depending on the situation there may be empirical ways of detecting and controlling for bias. Auguably, in the case at hand BBS roadside observations may be biasing the data. The best way of determining that is to survey areas in the same habitats using the very same BBS methodology (e.g., size of spatial unit, number of observations per route), but without the roadside observations. If we find that these alternative areas produce findings similar to that of the BBS we can be more confident in the BBS results. If there are significant differences we can either control for the differences in the BBS findings or alter the BBS methodology. Third, given that the BBS data are flawed assigning probability levels to differences is not without difficulty and I would be uncomfortable with any but the most conservative probability standard. Even with high quality data our interest in science is mainly with differences that are "important," not ones that are merely significant. Flawed data for which differences are only significant at the .05 level are the most likely to be overturned. And of course, any suggestion a trend may exist even though the difference is not significant at the .05 level is spurious by definition. So what I think we can take away from the BBS results are findings that show important differences, as in the case of birds such as Bewick's Wren, Loggerhead Shrike, Golden-winged Warbler, Yellow Warbler, etc.. Beyond important differences we are asking more than the data will allow. Note that Bill makes a point of highlighting the most important findings, and he may want to give us more confidence in the results by using more conservative summary statistics in developing the lists of increasing and declining species. Fourth, the size and "selection" of the study period may be a concern for some. Forty-five years may seem like a lot but with these low-sample time-series data it is very difficult to generalize beyond the period of study. Thus, for example, if we had BBS data from 1956 instead of 1966 it is possible that the findings would have been different. (For some declining species the 1966 inauguration date may seriously underestimate the degree of decline.) Similarly, the findings might well be different in 2020. Note that these data can be "convenient" or ad hoc in another way. What we would really like are start-and-stop times that are meaningful to the substantive issues under discussion. For example, one useful moment to begin analyses of climate change is the historical development of industriatization. Meaningful temporal periods provide for focused theoretical discussion, predictive modeling and causal attribution. Especially if we are interested in bird populations as a whole, I would much rather see--not that I will get the chance--BBS data from 1966 to 2066 or even 2100, 100 and 134 years with which we will have more information about the success of bird populations. Fifth, disaggregate, disaggregate, disaggregate! (Or analyze, analyze, analyze to use the Greek derivation.) Studies like BBS give us a great deal of information but if there is any methodological prescription we should have learned by now it is that we produce the best science by "disaggregating." Thorough research on individual species will always trump more superficial research on large numbers of species. After all, and those who use BBS data uniformly agree, we really want to know much more than which species are increasing or decreasing. Finally, if we believe that our methods and theories are set in concrete we are not doing science. Our obligation, our "calling" (to borrow a term from The Big Year), is to try to produce better science in the future. There are few areas in which the last word has been said. In science last words are for those who have nothing else to say. Thanks again to Bill for his strong contribution, and to the others who added to this most interesting discussion, the best kind of midterm break possible. And with a first Eurasian Wigeon in Arkansas just a few miles from Memphis, and a major movie on birding what's not to like? Kevin Breault Brentwood, TN