Hypothesis 2: Exposure to elements based on relation to other trees or landscape position

[mcgregorian1]

H2- Large trees suffer more during drought because of greater exposure (to radiation, wind, etc.)--either in relation to neighboring trees or because of position on landscape

P2a- Trees currently in a canopy position suffered more during drought. If canopy position is more important than height, we'd expect current canopy position to be a better predictor than current height. Preliminary results : This is true; inclusion of canopy position improves statistical model, but the effect is not nearly as strong as height at time of drought (#6). Caveat: canopy position and height are strongly linked, and height at time of drought may be a better descriptor of past canopy position than is current canopy position. Preliminary conclusion: Drought sensitivity differs by canopy position, but this may be just because of its correlation with height. Preliminary conclusion: Height itself is more important than canopy position.

P2b- Current canopy position will improve model over just the effect of height. Better comparison if we use current height. *Preliminary results :

• This is not supported for all 3 droughts combined; inclusion of canopy position along with height increases AIC by ~1.5 (#6).
• Not supported for 1966 drought (see here).
• This is supported for just the most recent drought analyzed (1999; see here)*

Caveat: The study design makes it so that we're prone to type II error (false negative). This is because we're going off of current canopy position. Some trees currently in a dominant/co-dominant position were probably in an intermediate/suppressed position at the time of drought, but the reverse is unlikely to be true. This weakens the separation between canopy and subcanopy individuals Preliminary conclusion: Canopy position is important, but only in the most recent drought-- presumably because current canopy position is not a reliable indicator of canopy position >40-50 years prior.

Next step:

• [x] try a model with just current height (+ random effects) to see if it is a better predictor than just current canopy position (+ random effects).

P2c-Trees at higher elevations--particularly tall trees--suffer more because they are more exposed. Thus, elevation has additive or interactive effect with that of height (model with height + / elevation better predictor than just height.) Preliminary results : Including elevation in model along with [dbh] or [dbh+canopy] sometimes improves the model (#6, #9). Effect is positive but weak Next step:*

• [x] try a model with dbh*elev (+ random effects) to see if there is an interaction. Be sure to note direction of interaction, as this will differentiate between H2 and H3 (see below).

Originally posted by @teixeirak's writing in issue #7

[mcgregorian1]

Adding in historical height with just random effects gives us a much stronger prediction than canopy position with random effects.

R-squared is 0.156

R-squared is 0.132

[mcgregorian1]

1999

Height makes the model better, but position is still in the top two. R2 is 0.18.

1977

already in 1977 we see the effect of current canopy position not matter as much.

1966

grows wider for 1966 and presumably 1964

[mcgregorian1]

P2c

This interaction between dbh and elev_m was tested in #14 for P2b. I'm marking it as done here.

[teixeirak]

I think we're done with this issue.