Data are the number of species observed in a 0.25 m^2 plot. The original data include the number of stems and percentage cover of each species within the sampling plot. Data collected by Gerry Koza (koz7133@calu.edu) in the summer 2017.

wetlands

Format

A data frame with 78 rows and 5 variables:

site

Gameland

wetland

Wetland number. Can be 1 2 or3

Plot

Transect an plot designations

water.depth

depth of water within sapling plot

spp.richness

The number of species observed within the sampling plot

Examples

## Load packages library(ggplot2) library(ggpubr) ## Set wetland as a factor wetlands$wetland <- factor(wetlands$wetland) ## Explore data graphically ### Plot boxplots ggboxplot(data = wetlands, y = "spp.richness", x = "wetland", fill = "wetland") ### Plot histograms gghistogram(data = wetlands, x = "spp.richness", title = "All data") g ghistogram(data = wetlands, x = "spp.richness", facet.by = "wetland", fill = "wetland", title = "Faceted by wetland") ## Plot means with 95% confidence intervals ggerrorplot(wetlands, x = "wetland", y = "spp.richness", desc_stat = "mean_ci", add = "mean") ## 1-way ANOVA ### null model model.null <- lm(spp.richness ~ 1, data = wetlands) ### model of interest model.alt <- lm(spp.richness ~ wetland, data = wetlands) ### compare models anova(model.null, model.alt) ## Pairwise comparisons after 1-way ANOVA ### no corrections for multiple comparisons pairwise.t.test(x = wetlands$spp.richness, g = wetlands$wetland, p.adjust.method = "none") ### Bonferonni correction pairwise.t.test(x = wetlands$spp.richness, g = wetlands$wetland, p.adjust.method = "bonferroni") ## Tukey test ### re-fit model with aov() model.alt.aov <- aov(spp.richness ~ wetland, data = wetlands) ### TukeyHSD() on model from aov() TukeyHSD(model.alt.aov) ### Plot effect sizes plotTukeysHSD(TukeyHSD(model.alt.aov))
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