Rate of change between consecutive time steps at each location — how fast
conditions are shifting, as distinct from what they currently are. A water mass
warming rapidly is a different habitat from one sitting at the same temperature.
Usage
temporal_gradient(
env_dat,
vars = NULL,
per = c("step", "day", "month"),
suffix = "_tgrad"
)
Arguments
- env_dat
an sf POINT object with one row per location and time step,
as datamatch's access functions return
- vars
covariate columns to differentiate; NULL does all of them
- per
time unit for the rate: "step" (default, change per time step),
"day", or "month"
- suffix
suffix for the new columns
Value
env_dat with a <var>_tgrad column per covariate
Details
The first time step has no predecessor and is NA.
Examples
if (FALSE) { # \dontrun{
env <- temporal_gradient(env, "SST") # change per time step
env <- temporal_gradient(env, "SST", per = "day") # degrees C per day
} # }