% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/biomass.R
\docType{data}
\name{Biomass}
\alias{Biomass}
\title{Biomass Allocation in Two Grass Species Under Different Nitrate Supply}
\format{
A data frame with 500 observations and 13 variables:
\describe{
  \item{species_name}{Species code (DfH, DfL, HlH, HlL) where:
    \itemize{
      \item DfH = D. flexuosa (slow-growing), high nitrate
      \item DfL = D. flexuosa (slow-growing), low nitrate
      \item HlH = H. lanatus (fast-growing), high nitrate
      \item HlL = H. lanatus (fast-growing), low nitrate
    }
  }
  \item{species}{Species scientific name (D. flexuosa or H. lanatus)}
  \item{trt}{Nitrate treatment level (high or low)}
  \item{day}{Experimental day (0 to 49)}
  \item{pl_num}{Plant number (individual plant identifier, 6-8 replicates per treatment)}
  \item{ldm_mg}{Leaf dry mass (mg)}
  \item{sdm_mg}{Stem dry mass (mg)}
  \item{rdm_mg}{Root dry mass (mg)}
  \item{tdm_mg}{Total dry mass (mg)}
  \item{lmf}{Leaf mass fraction - proportion of biomass allocated to leaves (0-1)}
  \item{smf}{Stem mass fraction - proportion of biomass allocated to stems (0-1)}
  \item{rmf}{Root mass fraction - proportion of biomass allocated to roots (0-1)}
  \item{ln_tdm}{Natural log of total dry mass (log-transformed for allometric analysis)}
}
}
\source{
Data originally made available by bobdouma (2019) at
\doi{10.5281/zenodo.3234670}, derived from the
experiment described in:

Poorter, H., van de Vijver, C.A.D.M., Boot, R.G.A. & Lambers, H. (1995)
Growth and carbon economy of a fast-growing and a slow-growing grass species
as dependent on nitrate supply. \emph{Plant and Soil}, 171, 217-227.

Poorter, H. & Sack, L. (2012) Pitfalls and possibilities in the analysis of
biomass allocation patterns in plants. \emph{Frontiers in Plant Science},
3, 259.
}
\usage{
data(Biomass)
}
\description{
This dataset examines biomass allocation patterns in plants, specifically
the proportional distribution of biomass to different plant organs (stems,
leaves, and roots). The data come from an experiment manipulating nitrate
supply in fast-growing and slow-growing grass species.

The response variables (stem, leaves, roots) are proportions bounded in the
(0,1) interval, making them suitable for simplex regression analysis.
}
\examples{
# Load the data
data(Biomass)

# Quick overview
head(Biomass)
str(Biomass)

# Check that proportions sum to 1 (within rounding error)
summary(rowSums(Biomass[, c("lmf", "smf", "rmf")]))

# Simple plot of root mass fraction by treatment
boxplot(rmf ~ trt * species, data = Biomass,
        main = "Root Mass Fraction by Species and Nitrate Treatment",
        las = 2)
}
\references{
When using this data, please cite:

bobdouma (2019) \emph{bobdouma/proportions_beta_Dirichlet: v.01}.
\doi{10.5281/zenodo.3234670}.

Poorter, H. & Sack, L. (2012) Pitfalls and possibilities in the analysis of
biomass allocation patterns in plants. \emph{Frontiers in Plant Science},
3, 259. \doi{10.3389/fpls.2012.00259}
}
\keyword{datasets}
