Dung nutrient data of rabbit, fallow deer, horse, cow, and European bison
Data files
Feb 28, 2024 version files 2.83 KB
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physicochemical_characteristics.csv
1.45 KB
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README.md
1.39 KB
Mar 26, 2024 version files 2.83 KB
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physicochemical_characteristics.csv
1.42 KB
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README.md
1.41 KB
Abstract
Dung samples of European bison (Bison bonasus L.), cow (Bos taurus L.), fallow deer (Dama dama L.), horse (Equus ferus caballus L.), and rabbit (Oryctolagus cuniculus L.) were collected at the National Park Zuid-Kennemerland, the Netherlands (52.3961°N, 4.5921°E) on February 25th, 2020. The fresh herbivore dung was placed in the oven at 70 ℃ for 72 h for drying to measure the moisture and then ground for the measurement of the nutrients (Nitrogen, Carbon, Phosphorus, C:N, N:P). Total C concentrations were analyzed with a dry combustion analyzer (LECO CNS-2000). Total N concentrations were measured on an elemental analyzer (Thermo EA Flash 1112). Total P concentrations were analyzed using a modification of the combustion and hot HCl extraction procedure. Differences among species in dung nutrients were determined using a one-way ANOVA and Scheffe test in the agricolae package in R.
README: Dung nutrient data of rabbit, fallow deer, horse, cow and European bison
https://doi.org/10.5061/dryad.x95x69pqn
Nitrogen, Carbon, Phosphorus, C:N, N:P of the dung nutrient composition of five herbivore species living in the European coastal dune ecosystem.
Description of the data structure
This is a dataframe with 7 columns (moisture, TC, TN, TP, C:N, N:P, herbivore species) and 20 rows (each herbivore species has four independent individual samples). Moisture's unit is (%); TC, TN and TP's units are (g/kg). This dataframe only includes the original nutrient data without statistical analysis, if you need the final analyzed data please read the article "Microbial community composition in the dung of five sympatric European herbivore species" published in Ecology and Evolution, or conduct the R codes below in your PC.
R Code
setwd("C:/Users/...")
library(agricolae) ## for scheffe.test()
physico <- read.csv("physicochemical characteristics.csv")
run_analysis <- function(data, variable) {
formula <- as.formula(paste(variable, "~ herbivore.species", sep = ""))
model <- aov(formula, data = data)
summary(model)
scheffe.test(model, "herbivore.species")
}
variables <- c("moisture", "tn", "tc", "tp", "c.n", "n.p")
results <- lapply(variables, function(var) {
cat("Analyzing", var, "\n")
run_analysis(physico, var)
})
results