- exclude
Two values (distance and duration) which allow users
to exclude short-duration long-lag climate windows from analysis (e.g.,
windows with a duration of 10 days which occur over a month ago).
These windows are often considered to be biologically implausible.
- repeats
The number of times that data will be randomised and analysed
for climate windows.
- window
Whether randomisations are carried out for a sliding window ("sliding")
or weighted window ("weighted") approach.
- xvar
A list object containing all climate variables 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 structure used for testing correlation.
Currently known to support lm, glm, lmer and glmer objects.
- stat
If window = "sliding"; 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 FUN in apply for more detail.
- range
Two values signifying respectively the furthest and closest number
of time intervals (set by cinterval) back from the cutoff date or biological record to include
in the climate window search.
- func
The functions used to fit the climate variable. Can be linear
("lin"), quadratic ("quad"), cubic ("cub"), inverse ("inv") or log ("log").
- type
"absolute" or "relative", whether you wish the climate window to be relative
(e.g. the number of days before each biological record is measured) or absolute
(e.g. number of days before a set point in time).
- refday
If type is absolute, the day and month respectively of the
year from which the absolute window analysis will start.
- cmissing
cmissing Determines what should be done if there are
missing climate data. Three approaches are possible:
- FALSE; the function will not run if missing climate data is encountered.
An object 'missing' will be returned containing the dates of missing climate.
- "method1"; missing climate data will be replaced with the mean climate
of the preceding and following 2 days.
- "method2"; missing climate data will be replaced with the mean climate
of all records on the same date.
- cinterval
The resolution at which climate window analysis will be
conducted. May be days ("day"), weeks ("week"), or months ("month"). Note the units
of parameter 'range' will differ depending on the choice
of cinterval.
- spatial
A list item containing:
1. A factor that defines which spatial group (i.e. population) each biological
record is taken from. The length of this factor should correspond to the length
of the biological dataset.
2. A factor that defines which spatial group (i.e. population) climate data
corresponds to. This length of this factor should correspond to the length of
the climate dataset.
- cohort
A variable used to group biological records that occur in the same biological
season but cover multiple years (e.g. southern hemisphere breeding season). Only required
when type is "absolute". The cohort variable should be in the same dataset as the variable bdate.
- upper
Cut-off values 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, climatewin will instead calculate an
optimal climate zone.
- lower
Cut-off values used to determine chill days or negative
climate thresholds (depending on parameter thresh). Note that when values
of lower and upper are both provided, climatewin will instead calculate an
optimal climate zone.
- binary
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
A list item containing:
1. The variable used for mean centring (e.g. Year, Site, Individual).
Please specify the parent environment and variable name (e.g. Biol$Year).
2. Whether the model should include both within-group means and variance ("both"),
only within-group means ("mean"), or only within-group variance ("dev").
- k
If window = "sliding"; the number of folds used for k-fold cross validation. By default
this value is set to 0, so no cross validation occurs. Value should be a
minimum of 2 for cross validation to occur.
- weightfunc
If window = "weighted";
the distribution to be used for optimisation. Can be
either a Weibull ("W") or Generalised Extreme Value distribution ("G").
- par
If window = "weighted"; the shape, scale and location parameters
of the Weibull or GEV weight function used as start weight function.
For Weibull : Shape and scale parameters must be greater than 0,
while location parameter must be less than or equal to 0.
For GEV : Scale parameter must be greater than 0.
- control
If window = "weighted";
parameters used to determine step size for the optimisation
function. Please see optim for more detail.
- method
If window = "weighted";
the method used for the optimisation function. Please see
optim for more detail.
- cutoff.day, cutoff.month
Redundant parameters. Now replaced by refday.
- furthest, closest
Redundant parameters. Now replaced by range.
- thresh
Redundant parameter. Now replaced by binary.
- cvk
Redundant parameter. Now replaced by k.