[R-sig-eco] Question about a resampling procedure with LME

[Thierry Onkelinx]

Dear Thiago,

A few remarks.

Two pools are not enough to get reliable estimates for the random effect.
Although it is conceptually a random effect, it is better to use it as a
fixed effect.

At which level did you sample the bird diversity? I assume that it would be
much larger than 10 x 15 cm.  Is it a pool level or a smaller section of
the pool. Do you have coordinates of the sampling locations of both
zooplankton and the birds?

Best regards,

Thierry

ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium

To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to say
what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of data.
~ John Tukey

2016-11-14 3:28 GMT+01:00 Thiago Gonçalves-Souza <tgoncalves.souza at gmail.com
>:

> Hello all,
>
>
>
> First, I'm sorry for this long question, guys.
>
>
> I’d like to know if the diversity of waterbirds affect zooplankton
> diversity in natural temporary pools over two seasonal periods (wet and
> dry). I’ve sampled zooplankton in 38 10x15 cm plots on the pool’s shore
> sediment (in the same place where birds usually) in both seasonal periods.
> I used a model of bird feet and simulated them walking on the sediment of
> each plot. Then, I washed the bird feet (of each plot separately) into
> containers with filtered water. The zooplankton that emerged from this
> water were identified.
>
>
> Unfortunately, I was not able to collect birds at the same plot (and at the
> same time) that I simulated their footprint. Rather, I’ve made 38 samples
> (during 9 months immediately after each seasonal period) of bird
> communities (direct observation on each pool).
>
>
> Thus, I do not believe that can use any classic model (such as anova
> designs) because birds and zooplankton were not collected at the same
> sampling unit.
>
> To do this, I thought to randomly select *10* plots of each combination of
> zooplankton sampling, that is: 10 samples from pool 1/wet season, 10 from
> pool 1/dry season, 10 from pool 2/wet season and 10 from pool 2/dry season.
> I did the same with bird samples, selecting 10 samples by pool and season
> combination. Then, we run a lme model using species richness of birds
> (independent variable) and zooplankton (dependent variable), and season as
> independent variable. The variables were nested in pool. I repeated (for
> loop) this procedure 1000 times and calculated the number of times that the
> model was significant (p < 0.05) and the accompanying F values (for bird
> richness and season effects).
>
>
> I’d like to hear from you if this procedure make any sense. Please, see
> below a reproducible example. Thank you very much!
>
>
> Note: I’m pretty sure that the for loop could be shorter ;)
>
>
>
> library(nlme)
>
>
>
> #### Fake da ta
>
>
>
> ## zooplankton table
>
> ric.zoo <- rnorm(120, 20, 2)
>
> pool <- factor(rep(c("pool1", "pool2"), 60))
>
> season <- factor(rep(rep(c("dry", "wet"), each=30), 2))
>
> tab <- data.frame(pool, season, ric.zoo)
>
>
>
> ## birds table
>
> ric.bird <- rnorm(76, 10, 2)
>
> pool_b <- factor(rep(c("pool1", "pool2"), 38))
>
> season_b <- factor(rep(rep(c("dry", "wet"), each=19), 2))
>
> tab_b <- data.frame(pool=pool_b, season=season_b, ric.bird)
>
>
>
> ## Dataset to be used in for loops
>
> bird.p.val <- numeric()
>
> season.p.val <- numeric()
>
> bird.f <- numeric()
>
> season.f <- numeric()
>
> pool.sort <- rep(c("pool1", "pool2"), each=20)
>
> season.sort <- rep(rep(c("wet", "dry"), each=10), 2)
>
> factor.sort <- data.frame(pool=pool.sort, season=season.sort)
>
> nreps <- 1000
>
>
>
>
>
> for(i in 1:nreps){
>
>   subset1 <- subset(tab, pool=="pool1"&season=="wet")
>
>   subsample1 <- subset1[sample(nrow(subset1), 10),][,3]
>
>   subset2 <- subset(tab, pool=="pool1"&season=="dry")
>
>   subsample2 <- subset2[sample(nrow(subset2), 10),][,3]
>
>   subset3 <- subset(tab, pool=="pool2"&season=="wet")
>
>   subsample3 <- subset3[sample(nrow(subset3), 10),][,3]
>
>   subset4 <- subset(tab, pool=="pool2"&season=="dry")
>
>   subsample4 <- subset4[sample(nrow(subset4), 10),][,3]
>
>   subbird1 <- subset(tab_b, pool=="pool1"&season=="wet")
>
>   subsbird1 <- subbird1[sample(nrow(subbird1), 10),][,3]
>
>   subbird2 <- subset(tab_b, pool=="pool1"&season=="dry")
>
>   subsbird2 <- subbird2[sample(nrow(subbird2), 10),][,3]
>
>   subbird3 <- subset(tab_b, pool=="pool2"&season=="wet")
>
>   subsbird3 <- subbird3[sample(nrow(subbird3), 10),][,3]
>
>   subbird4 <- subset(tab_b, pool=="pool2"&season=="dry")
>
>   subsbird4 <- subbird4[sample(nrow(subbird4), 10),][,3]
>
>   ric.sort.zoo <- c(subsample1, subsample2, subsample3, subsample4)
>
>   ric.sort.birds <- c(subsbird1, subsbird2, subsbird3, subsbird4)
>
>   df40 <- data.frame(ric.zoo=ric.sort.zoo, ric.bird=ric.sort.birds,
> factor.sort)
>
>   lm.nested <- lme(ric.zoo~ric.bird+season, random=~1|pool, data=df40,
> method="REML")#MODELO
>
>   mod <- anova.lme(lm.nested, type="sequential", adjustSigma = FALSE)
>
>   bird.p.val[i] <- mod$`p-value`[2]
>
>   season.p.val[i] <- mod$`p-value`[3]
>
>   bird.f[i] <- mod$`F-value`[2]
>
>   season.f[i] <- mod$`F-value`[3]
>
> }
>
>
>
>
>
> sum(bird.p.val<0.05 )/nreps
>
> sum(season.p.val<0.05)/nreps
>
> --
>
> *Thiago Gonçalves-SouzaProfessor Adjunto*
>
> *Universidade Federal Rural de Pernambuco (UFRPE)*
> *Departamento de Biologia / Área de Ecologia *
>
> *E-mail alternativo: thiagoaracno at gmail.com <thiagoaracno at gmail.com>Home
> page:<http://thiagocalvesouza.wix.com/ecoffun
> <http://thiagocalvesouza.wix.com/ecoffun>**>*
> *Google Scholar:
> <http://scholar.google.com.br/citations?user=TjaP2l8AAAAJ&hl=pt-BR
> <http://scholar.google.com.br/citations?user=TjaP2l8AAAAJ&hl=pt-BR>>*
>
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>
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