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bobmuscarella / Panama_analysis

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How to handle growth outliers? #1

Open bobmuscarella opened 8 years ago

bobmuscarella commented 8 years ago

For now, just leave them and see if it gives problems with convergence...

Alternatively, select a standard deviation and say it is probably measurement error? e.g. tdata$Growth.Include <- abs(tdata$growth) < (sd(tdata$growth, na.rm=T) * 15)

tdata$Growth.Include[is.na(tdata$growth)] <- F

bobmuscarella commented 8 years ago

There is precidence for dealing with this from Condit et al. 2004 (Tropical forest dynamics across a rainfall gradient...):

Before estimating growth, we discarded negative increments where the second dbh was 4 SD1 below the first, since these were most likely due to the second type of error [measurement on wrong tree]. The same correction cannot be applied to positive outliers, since trees grow. The fastest growing species at BCI, Trema micrantha and Ochroma pyrimidale, grew by as much as 30-50 mm y-1, with a few valid records as high as 70 mm y-1 (valid because successive dbh measures from 1982 to 2000 showed consistently high growth). We thus exclude any record > 75 mm y-1 as an error.

Condit, R., Aguilar, S., Hernandez, A., Perez, R., Lao, S., Angehr, G., Hubbell, S.P. & Foster, R.B. 2004. Tropical forest dynamics across a rainfall gradient and the impact of an El Niño dry season. Journal of Tropical Ecology 20: 51-72.

bobmuscarella commented 8 years ago

I've implemented the Condit et al. growth outlier exclusion in a column called $Growth.Include.2. Whereas the previous method (eliminating based on a fixed SD (e.g., 5*sd(tdata$growth)) would eliminate relatively high and low values, the Condit method tends to exclude stems with high negative growth but few observations of high growth (except for 'extreme' outliers).