‘I know that scotch and sunshine have an effect on me’ — Hah! Perfect ðŸ™‚

In all seriousness — yes, we’d want to see this repeated (with statistical significance this time!), as well as have a mechanism.

]]>It’s been years since I have I mucked in statistics but correlation is still miles from causality.

]]>I did a few more tests. First, I tried a random phase Monte Carlo. For my emulation of their correlation between ring width and GCR, I got r = 0.40, p = 0.12 for n = 10,000 phase randomized simulations.

Alternatively, if I account for the autocorrelation in both ring width and in the GCR data, I get a critical r-value for a = 0.05 of r = 0.55 and an estimated p = 0.14.

]]>Thanks — n(1-r)/(1+r) is a common way to adjust for autocorrelation, although as one approaches larger r values it will indeed become very (perhaps too) conservative. I’ll be interested to take a look at your code. Another approach would be some sort of phase randomizing Monte Carlo method to estimate the p value for the correlation of the actual data. I’ll try this if I get some time. Perhaps Eddy can weigh in on this as well.

On the issue of the plantation, while you are right that if you were looking for a sunlight signal in tree ring you would want to choose a site that was unlikely to be temperature or precipitation limited, my concern would be that a managed forest or plantation is going to have some potentially undesirable growth patterns due to competition (between trees) or management practices (i.e. thinning). Without the data, all I could do is speculate about the specific features of the Dengel chronology that could be related to stand dynamics (either intentional thinning or other management practices or release/suppression interactions between trees), and I don’t want to do that. But in general the concern is that non-climatic (including light) factors could be influencing tree growth in a planted, managed forest of young, non native trees.

]]>I am also not sure you can critisise the authors for choosing a plantation. If you want to investigate the effects of sky conditions on forests, then choosing a site where climate affects are weak would make sense.

library(nlme)

rho<-c(none=.000001,low=.1,moderate=.3,moderatehigh=.6,high=.9)

res<-lapply(rho,function(rx){##slow – time for coffee

n=100

x<-arima.sim(list(ar=rx),n=n)

sapply(rho,function(ry){

n2<-n*(1-ry)/(1+ry)#effective number of df

res<-replicate(500,{

y<-arima.sim(list(ar=ry),n=n)

r<-cor(x,y)

stat<-sqrt(n-2)*r/sqrt(1-r^2)

stat2<-sqrt(n2-2)*r/sqrt(1-r^2)

mod <- gls(y ~ x, correlation = corAR1(), method = "ML")

c(pearson=pt(stat,n-2),correctedpearson=pt(stat2,n2-2), gls=anova(mod)$p[2])

})

rowMeans(res<.05)

})

})

res

I considered submitting a comment to New Phytologist, but the cost/benefit makes it a little difficult to justify taking the time to do it. For example, Dengel et al got a fair bit of press for this. If i were to submit a comment, it would go back and forth between myself, reviewers, and the editorial board for several months. If it passes review, it will get stuck in the back of an issue maybe a year from now, long past the time that people are even talking about GCR and tree rings. It’s just not worth the effort (for me, anyway).

In the end, I’ve found the literature to be pretty good at self correcting. Considering the difficulty that anyone will have reproducing their results with proper statistics and study design, I think this stuff will disappear off the radar pretty soon.

]]>The paper, in its rush to account for the correlation between rings and rays, forgets that the cosmic radiation is controlled by solar activity, and that this solar activity could more directly affect tree growth. I don’t subscribe to this, but it is more plausible that a direct effect of rays.

Climate skeptics have begun to notice this paper. Always desperate to accept any work, however risible, that they believe supports their position, and any flaw, however minute (or imaginary) in the rest of the literature.

]]>