photosynthesis (version 2.1.5)

fit_hydra_vuln_curve: Fitting hydraulic vulnerability curves

Description

Fitting hydraulic vulnerability curves

Usage

fit_hydra_vuln_curve(
  data,
  varnames = list(psi = "psi", PLC = "PLC"),
  start_weibull = list(a = 2, b = 2),
  title = NULL
)

Value

fit_hydra_vuln_curve fits a sigmoidal function (Pammenter & Van der Willigen, 1998) linearized according to Ogle et al. (2009). Output is a list containing the sigmoidal model in element 1 and Weibull model in element 4, the fit parameters with 95% confidence interval for both models are in element 2, and hydraulic parameters in element 3 (including P25, P50, P88, P95, S50, Pe, Pmax, DSI). Px (25 to 95): water potential at which x% of conductivity is lost. S50: slope at 50% loss of conductivity. Pe: air entry point. Pmax: hydraulic failure threshold. DSI: drought stress interval. Element 5 is a graph showing the fit, P50, Pe, and Pmax.

Arguments

data

Dataframe

varnames

List of variable names. varnames = list(psi = "psi", PLC = "PLC") where psi is water potential in MPa, and PLC is percent loss conductivity.

start_weibull

starting values for the nls fitting routine for the Weibull curve

title

Title for the output graph

References

Ogle K, Barber JJ, Willson C, Thompson B. 2009. Hierarchical statistical modeling of xylem vulnerability to cavitation. New Phytologist 182:541-554

Pammenter NW, Van der Willigen CV. 1998. A mathematical and statistical analysis of the curves illustrating vulnerability of xylem to cavitation. Tree Physiology 18:589-593

Examples

# \donttest{
# Read in data
data <- read.csv(system.file("extdata", "hydraulic_vulnerability.csv",
  package = "photosynthesis"
))

# Fit hydraulic vulnerability curve
fit <- fit_hydra_vuln_curve(data[data$Tree == 4 & data$Plot == "Control", ],
  varnames = list(
    psi = "P",
    PLC = "PLC"
  ),
  title = "Control 4"
)

# Return Sigmoidal model summary
summary(fit[[1]])

# Return Weibull model summary
summary(fit[[4]])

# Return model parameters with 95\% confidence intervals
fit[[2]]

# Return hydraulic parameters
fit[[3]]

# Return graph
fit[[5]]

# Fit many curves
fits <- fit_many(
  data = data,
  varnames = list(
    psi = "P",
    PLC = "PLC"
  ),
  group = "Tree",
  funct = fit_hydra_vuln_curve
)

# To select individuals from the many fits
# Return model summary
summary(fits[[1]][[1]]) # Returns model summary

# Return sigmoidal model output
fits[[1]][[2]]

# Return hydraulic parameters
fits[[1]][[3]]

# Return graph
fits[[1]][[5]]

# Compile parameter outputs
pars <- compile_data(
  data = fits,
  output_type = "dataframe",
  list_element = 3
)

# Compile graphs
graphs <- compile_data(
  data = fits,
  output_type = "list",
  list_element = 5
)
# }