Percent ground cover of herbage species and nettles.

Format

A data frame with 78 observations on the following 4 variables.

block: block, 6 levels
gen: genotype, 13 levels
nettle: percent ground cover of nettles
herb: percent ground cover of herbage species

Details

On the University of Nottingham farm, 13 different strains and species of herbage plants were sown on about 4 acres in an RCB design. Each grass species was sown together with white clover seed.

During establishment of the herbage plants, it became apparent that Urtica dioica (nettle) became established according to the particular herbage plant in each plot. In particular, nettle became established in plots sown with leguminous species and the two grass species. The graminaceous plots had less nettles.

The data here are the percentage ground cover of nettle and herbage plants in September 1951.

Note, some of the percent ground cover amounts were originally reported as 'trace'. These have been arbitrarily set to 0.1 in this data.

gen	species	strain
G01	Lolium perenne	Irish perennial ryegrass
G02	Lolium perenne	S. 23 perennial ryegrass
G03	Dactylis glomerata	Danish cocksfoot
G04	Dactylis glomerata	S. 143 cocksfoot
G05	Phleum pratense	American timothy
G06	Phleum pratense	S. 48 timothy
G07	Festuca pratensis	S. 215 meadow fescue
G08	Poa trivialis	Danish rough stalked meadow grass
G09	Cynosurus cristatus	New Zealand crested dogstail
G10	Trifolium pratense	Montgomery late red clover
G11	Medicago lupulina	Commercial black medick
G12	Trifolium repens	S. 100 white clover
G13	Plantago lanceolata	Commercial ribwort plantain

Source

Ivins, JD. (1952). Concerning the Ecology of Urtica Dioica L., Journal of Ecology, 40, 380-382. https://doi.org/10.2307/2256806

References

Ivins, JD (1950). Weeds in relation to the establishment of the Ley. Grass and Forage Science, 5, 237--242. https://doi.org/10.1111/j.1365-2494.1950.tb01287.x

O'Gorman, T.W. (2001). A comparison of the F-test, Friedman's test, and several aligned rank tests for the analysis of randomized complete blocks. Journal of agricultural, biological, and environmental statistics, 6, 367--378. https://doi.org/10.1198/108571101317096578

Examples


library(agridat)

data(ivins.herbs)
dat <- ivins.herbs

# Nettle is primarily established in legumes.
libs(lattice)
xyplot(herb~nettle|gen, dat, main="ivins.herbs - herb yield vs weeds",
       xlab="Percent groundcover in nettles",
       ylab="Percent groundcover in herbs")

# O'Brien used first 7 species to test gen differences
dat7 <- droplevels(subset(dat, is.element(gen, c('G01','G02','G03','G04','G05','G06','G07'))))
m1 <- lm(herb ~ gen + block, data=dat7)
anova(m1) # gen p-value is .041
#> Analysis of Variance Table
#> 
#> Response: herb
#>           Df  Sum Sq Mean Sq F value  Pr(>F)  
#> gen        6 1083.24 180.540  2.5518 0.04072 *
#> block      5  590.69 118.138  1.6698 0.17236  
#> Residuals 30 2122.48  70.749                  
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Response: herb
##           Df  Sum Sq Mean Sq F value  Pr(>F)
## gen        6 1083.24 180.540  2.5518 0.04072 *
## block      5  590.69 118.138  1.6698 0.17236
## Residuals 30 2122.48  70.749

friedman.test(herb ~ gen|block, dat7) # gen p-value .056
#> 
#> 	Friedman rank sum test
#> 
#> data:  herb and gen and block
#> Friedman chi-squared = 12.286, df = 6, p-value = 0.05589
#>