"None of this is going to settle any issues of "blame" for neonics.  What it will do is establish credibility for the work as a whole, or make clear that the work is not credible. "

No.  It won't establish "credibility", rather, it will establish a database of dosages at which either harm, or no harm, was shown.  THEN come other layers...what other bee stressors were present?  What other factors work together with the neonics to explain the variability in outcomes?

We should not assume that "some did it right and others did it wrong".  Most peer-reviewed published studies were done by well-trained scientists and it is a waste of time to start by making the assumption (when data don't correlate between studies)  that the scientists don't know their business.  Poorly done studies are more the exception than the rule, in spite of what many would have us think.

PeterD is right when he says:

"Whilst the focus was on "does smoking cause lung cancer?", with much to and fro debate and research pointing both ways,  people were succumbing to accelerated rates of heart disease, stroke, peripheral vascular disease etc which we now know was related to their smoking habit."

...and he is right also by pointing out that those who refuse to understand that because they personally have no problems with their bees and local agriculture, but others do, that consequently "the others" are not just victims of one disease, one chemical, or one management error.

I teach my research students that it is human nature to have tunnel vision where "why what how" is concerned, and we should ensure that multiple points of view are taken seriously.  The answer is not usually found by following just one train of thought.  There are layers to this bee health problem because synergies between chemicals, multiple bee stressors, and management are all factors to whether the result is a healthy colony or a dead one.  Unfortunately, too many want the solution to be in "black and white" and unfortunately, that works all too well for those selling us various "solutions".

So this project between Jim and myself, and others so inclined (please contact me for access to the papers) is the first step.  Will we see a scattergram when we plot dose versus % survival from multiple studies?  We expect so, and in that case, what is the next correlate we would impose on the data?  The spreadsheet will have to include more information in order to pursue this further.  If there is a trend, the answer will be fairly straightforward.  Such an outcome (trend) is unlikely given the raging debate on this topic (but I'm prepared to be surprised).  Having all of the relevant info on a spreadsheet, and being able to work the various parameters, is actually a valuable way to spend our time and to get closer to the heart of the problem, IMO.

Christina



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