foto | R Documentation |
The net carbon dioxide exchange of late successional moss species (Sphagnum fuscum) samples under seven levels of photosynthetic photon flux density in cronosequence of land uplift mires on the Finnish side of Bothnia Bay in Siikajoki, Finland. Moss samples were transplanted from the late succession site (Site 6) to all sites and photosynthetic activity was measured one year later for those samples which had survived.
data(foto)
A data frame with 455 observations on the following 8 variables.
Site
a factor with levels 1
,...,6 from the earliest successional stage to the latest
Treatment
a factor with value 1
for samples with competitor removal treatment
and 0
for untreated control.
sample
a factor with unique value for each of the 72 survived samples
moisture
moisture of the sample
PARtop
Photosyntetically active radiation (photon flux density μ mol /m^2 /s^2)
WT
water table, cm
A
Net CO2 exchange, μ {mol} / g / h,
subplot
a factor with unique value for each replicate
The number of transplanted replicates per site was 12, with two samples per replicate. One of the samples was treated with competing vegetation removal before transplanting whereas the other was left untreated. The 12 replicates per site were planted in locations with 2 to 3 different ground water table levels. A year after the transplanting, the photosynthetic activity (A) of the survived transplanted samples was recorded using seven artifically created light conditions ranging from complete darkness (PPFD=0) to extreme light conditions (PPFD=2000) using an open, fully controlled flow- through gas exchange fluorescence measurement system (GFS-3000; Walz, Effeltrich, Germany).
Laine, A.M., Ehonen, S., Juurola, E., Mehtatalo, L., and Tuittila, E-S. 2015. Performance of late succession species along a chronosequence: Environment does not exclude Sphagnum fuscum from the early stages of mire development. Journal of Vegetation Science 26(2): 291-301. doi: 10.1111/jvs.12231
Mehtatalo, Lauri and Lappi, Juha 2020. Biometry for Forestry and Environmental Data: with examples in R. New York: Chapman and Hall/CRC. 426 p. doi: 10.1201/9780429173462
data(foto) LightResp<-function(PPFD,alpha=0.1,Pmax=10,A0=0) { A0+Pmax*PPFD/(alpha+PPFD) } library(nlme) model5<-nlme(A~LightResp(PARtop,alpha,Pmax,A0), fixed=list(alpha~Site+Treatment+moisture,Pmax~Site+Treatment,A0~Site), random=list(sample=Pmax+alpha~1), data=foto, start=c(c(80,0,0,0,0,0,0,0),c(100,0,0,0,0,0,0),c(-20,0,0,0,0,0)), verbose=TRUE)
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