predatGM: Abundance data of predatory insects
In shearer/simboot: Simultaneous Inference for Diversity Indices
predatGM R Documentation
Abundance data of predatory insects
Description
In a field trial with 8 complete blocks, one genetically modified crop variety and three varieties without genetical modification (S1, S2, S3) have been cultivated.
Note that S1 is genetically closely related to the GM variety, and mainly differs from GM by not containing the transformation, while S2 and S3 are conventional varieties, which are genetically not closely related to GM and S1. In each of the 24 plots, a certain taxonomic group of predatory insects has been trapped. Trapped individuals have been classified to the species level. A total of 33 different species has been observed. For each plot, the summed counts of each species over one cultivation period is given in the variables Sp1, Sp2,...Sp33.
Among others, one question in research was: Does the genetic modified variety effect biodiversity of the (ecologically important, non-target) species?
Usage
data(predatGM)
Format
A data frame with 32 observations on the following 35 variables.
Blocka numeric vector, values 1,...,8 indicate the blocks of the trial
Varietya factor distinguishing the four varieties in the field trial, with levels GM (the genetically modified variety), S1 (the near-isogenic, conventional variety), S2 and S3 (further conventional varieties)
Sp1a numeric vector, observed counts of species 1
Sp2a numeric vector, ...
Sp3a numeric vector
Sp4a numeric vector
Sp5a numeric vector
Sp6a numeric vector
Sp7a numeric vector
Sp8a numeric vector
Sp9a numeric vector
Sp10a numeric vector
Sp11a numeric vector
Sp12a numeric vector
Sp13a numeric vector
Sp14a numeric vector
Sp15a numeric vector
Sp16a numeric vector
Sp17a numeric vector
Sp18a numeric vector
Sp19a numeric vector
Sp20a numeric vector
Sp21a numeric vector
Sp22a numeric vector
Sp23a numeric vector
Sp24a numeric vector
Sp25a numeric vector
Sp26a numeric vector
Sp27a numeric vector
Sp28a numeric vector
Sp29a numeric vector
Sp30a numeric vector
Sp31a numeric vector
Sp32a numeric vector
Sp33a numeric vector
Source
Data set provided by Kai U. Priesnitz, Bavarian State Research Center for Agriculture, Institute for Plant
Protection, Freising, Germany.
Examples
data(predatGM)
str(predatGM)
# Display data as a mosaicplot
# load("D:/Mueller/Biodiv/data/predatGM.rda")
# Matrix of counts with appropriate names
COUNTS<-as.matrix(predatGM[,3:35])
SPECNAM<-names(predatGM)[3:35]
colnames(COUNTS)<-SPECNAM
rownames(COUNTS)<-predatGM[,"Variety"]
# Assign colors and order by decreasing total abundance
COL<-grey(c(0,2,4,6,8,1,3,5,7)/8)
DMO<-COUNTS[,order(colSums(COUNTS), decreasing=TRUE)]
colnames(DMO)[15:33]<-"."
# Mosaicplot
par(mar=c(4,2,1,1))
mosaicplot(DMO, col=COL, las=2, off=15, main="", cex=1.1)
mtext("A", side=3, line=-1.5, adj=0, cex=2)
shearer/simboot documentation built on Feb. 13, 2024, 6:58 a.m.
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| predatGM | R Documentation |
Abundance data of predatory insects
Description
In a field trial with 8 complete blocks, one genetically modified crop variety and three varieties without genetical modification (S1, S2, S3) have been cultivated. Note that S1 is genetically closely related to the GM variety, and mainly differs from GM by not containing the transformation, while S2 and S3 are conventional varieties, which are genetically not closely related to GM and S1. In each of the 24 plots, a certain taxonomic group of predatory insects has been trapped. Trapped individuals have been classified to the species level. A total of 33 different species has been observed. For each plot, the summed counts of each species over one cultivation period is given in the variables Sp1, Sp2,...Sp33. Among others, one question in research was: Does the genetic modified variety effect biodiversity of the (ecologically important, non-target) species?
Usage
data(predatGM)Format
A data frame with 32 observations on the following 35 variables.
Blocka numeric vector, values 1,...,8 indicate the blocks of the trial
Varietya factor distinguishing the four varieties in the field trial, with levels
GM(the genetically modified variety),S1(the near-isogenic, conventional variety),S2andS3(further conventional varieties)Sp1a numeric vector, observed counts of species 1
Sp2a numeric vector, ...
Sp3a numeric vector
Sp4a numeric vector
Sp5a numeric vector
Sp6a numeric vector
Sp7a numeric vector
Sp8a numeric vector
Sp9a numeric vector
Sp10a numeric vector
Sp11a numeric vector
Sp12a numeric vector
Sp13a numeric vector
Sp14a numeric vector
Sp15a numeric vector
Sp16a numeric vector
Sp17a numeric vector
Sp18a numeric vector
Sp19a numeric vector
Sp20a numeric vector
Sp21a numeric vector
Sp22a numeric vector
Sp23a numeric vector
Sp24a numeric vector
Sp25a numeric vector
Sp26a numeric vector
Sp27a numeric vector
Sp28a numeric vector
Sp29a numeric vector
Sp30a numeric vector
Sp31a numeric vector
Sp32a numeric vector
Sp33a numeric vector
Source
Data set provided by Kai U. Priesnitz, Bavarian State Research Center for Agriculture, Institute for Plant Protection, Freising, Germany.
Examples
data(predatGM)
str(predatGM)
# Display data as a mosaicplot
# load("D:/Mueller/Biodiv/data/predatGM.rda")
# Matrix of counts with appropriate names
COUNTS<-as.matrix(predatGM[,3:35])
SPECNAM<-names(predatGM)[3:35]
colnames(COUNTS)<-SPECNAM
rownames(COUNTS)<-predatGM[,"Variety"]
# Assign colors and order by decreasing total abundance
COL<-grey(c(0,2,4,6,8,1,3,5,7)/8)
DMO<-COUNTS[,order(colSums(COUNTS), decreasing=TRUE)]
colnames(DMO)[15:33]<-"."
# Mosaicplot
par(mar=c(4,2,1,1))
mosaicplot(DMO, col=COL, las=2, off=15, main="", cex=1.1)
mtext("A", side=3, line=-1.5, adj=0, cex=2)
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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