Question: If var(leafout) is declining, then what does it mean if var(mat) is declining?

We know leafout date variance is declining massively -- if your y variable is declining in variance as your x variable declines in variance, I think you have to worry about both changes and they could cancel out ....

Here's a quick example where the variance in temp decreases:

corr <- rep(0.5, 6)
sdtemp <- c(8, 4, 2)
sdphen <- c(6,6,6)

for(i in 1:3){
print((corr[i]*sdphen[i])/sdtemp[i])
 }
[1] 0.375
[1] 0.75
[1] 1.5

And the 'sensitivity' goes up, but here I equally decrease the phenology variance:

corr <- rep(0.5, 6)
sdtemp <- c(8, 4, 2)
sdphen <- c(6,3,1.5)

for(i in 1:3){
print((corr[i]*sdphen[i])/sdtemp[i])
 }
[1] 0.375
[1] 0.375
[1] 0.375

lizzieinvancouver / decsens

Question: If var(leafout) is declining, then what does it mean if var(mat) is declining? #9