climwin (version 0.1.2)

autowin: Test for auto-correlation in climate.

Description

Tests the correlation between the climate in a specified climate window and other fitted climate windows.

Usage

autowin(reference, xvar, cdate, bdate, baseline, furthest, closest, stat, func,
  type, cutoff.day, cutoff.month, cmissing = FALSE, cinterval = "day",
  upper = NA, lower = NA, thresh = FALSE, centre = NULL)

Arguments

reference

Reference climate data to be compared. Generated by functions singlewin or climatewin.

xvar

The climate variable of interest. Please specify the parent environment and variable name (e.g. Climate$Temp).

cdate

The climate date variable (dd/mm/yyyy). Please specify the parent environment and variable name (e.g. Climate$Date).

bdate

The biological date variable (dd/mm/yyyy). Please specify the parent environment and variable name (e.g. Biol$Date).

baseline

The baseline model used to fit climate windows. These will be correlated with the reference climate window.

furthest

The furthest number of time intervals (set by cinterval) back from the cutoff date or biological record to include in the climate window search.

closest

The closest number of time intervals (set by cinterval) back from the cutoff date or biological record to include in the climate window search.

stat

The aggregate statistic used to analyse the climate data. Can currently use basic R statistics (e.g. mean, min), as well as slope. Additional aggregate statistics can be created using the format function(x) (...). See parameter FUN in

func

The function used to fit the climate variable. Can be linear ("lin"), quadratic ("quad"), cubic ("cub"), inverse ("inv") or log ("log"). Not required when a variable is provided for parameter 'centre'.

type

fixed or variable, whether you wish the climate window to be variable (e.g. the number of days before each biological record is measured) or fixed (e.g. number of days before a set point in time).

cutoff.day,cutoff.month

If type is fixed, the day and month of the year from which the fixed window analysis will start.

cmissing

TRUE or FALSE, determines what should be done if there are missing climate data. If FALSE, the function will not run if missing climate data is encountered. If TRUE, any records affected by missing climate data will be removed from climate window analy

cinterval

The resolution at which climate window analysis will be conducted. May be days ("day"), weeks ("week"), or months ("month"). Note the units of parameters 'furthest' and 'closest' will differ with the choice of cinterval.

upper

Cut-off value used to determine growing degree days or positive climate thresholds (depending on parameter thresh). Note that when values of lower and upper are both provided, autowin will instead calculate an optimal climate zone.

lower

Cut-off value used to determine chill days or negative climate thresholds (determined by parameter thresh). Note that when values of lower and upper are both provided, autowin will instead calculate an optimal climate zone.

thresh

TRUE or FALSE. Determines whether to use values of upper and lower to calculate binary climate data (thresh = TRUE), or to use for growing degree days (thresh = FALSE).

centre

Variable used for mean centring (e.g. Year, Site, Individual). Please specify the parent environment and variable name (e.g. Biol$Year).

Value

• Will return a data frame showing the correlation between the climate in each fitted window and the chosen reference window.

Examples

# Test for auto-correlation using 'Mass' and 'MassClimate' data frames

data(Mass)
data(MassClimate)

# Fit a single climate window using the datasets Mass and MassClimate.

single <- singlewin(xvar = list(Temp = MassClimate$Temp),
                    cdate = MassClimate$Date, bdate = Mass$Date,
                    baseline = lm(Mass ~ 1, data = Mass),
                    furthest = 72, closest = 15,
                    stat = "mean", func = "lin", type = "fixed",
                    cutoff.day = 20, cutoff.month = 5,
                    cmissing = FALSE, cinterval = "day")

# Test the autocorrelation between the climate in this single window and other climate windows.

auto <- autowin(reference = single$BestModelData$climate,
                xvar  = list(Temp = MassClimate$Temp), cdate = MassClimate$Date, bdate = Mass$Date,
                baseline = lm(Mass ~ 1, data = Mass), furthest = 365, closest = 0,
                stat = "mean", func = "lin",
                type = "fixed", cutoff.day = 20, cutoff.month = 5,
                cmissing = FALSE, cinterval = "day")

# View the output
head(auto)

# Plot the output
plotcor(auto, type = "A")