statespace_ed generates a time series of Euclidean distances from
defined reference conditions to assess the development of a suite of
ecological state indicators.
statespace_ed(x, time, ref_time = NULL, na_rm = TRUE)
| x | A data frame, tibble, matrix or vector of selected indicator(s). |
|---|---|
| time | A vector containing the actual time series. |
| ref_time | The reference time (single point in time, e.g. specific year) on which to base the Euclidean distance. Default is set to the first time point. |
| na_rm | A logical value indicating whether rows with NA values should be stripped before the computation proceeds. Default is set to TRUE. If set to FALSE and data contains NAs, the function returns NA. |
statespace_ed returns a tibble with the time vector time, the
Euclidean distance ed, and a logical vector ref_time indicating
the time step defined as reference.
This function implements an approach adopted from Tett et al. (2013) to assess changes in the ecosystem state by studying trajectories in state space. State space is defined here as the n-dimensional space of possible locations of state variables or indicators. For a robust suite of indicators the unidimensional Euclidean distance between each year (or any other time step) and a reference year in state space is calculated. That means, the function calculates the square root of the sum of squared distances between each standardized indicator value in a specific year and its reference value, which is defined by the user.
Tett, P., Gowen, R.J., Painting, S.J., Elliott, M., Forster, R., Mills, D.K., Bresnan, E., Capuzzo, E., Fernandes, T.F., Foden, J., Geider, R.J., Gilpin, L.C., Huxham, M., McQuatters-Gollop, A.L., Malcolm, S.J., Saux-Picart, S., Platt, T., Racault, M.F., Sathyendranath, S., van der Molen, J., Wilkinson, M. (2013) Framework for understanding marine ecosystem health. Marine Ecology Progress Series. 494, 1-27.
Other state assessment functions:
plot_statespace_ch(),
plot_statespace_ed(),
statespace_ch()
# Using the Baltic Sea demo data in the package ind_sel <- ind_ex[,c(2,3,4,8,10,11)] # --> selection of complementary and well performing indicators # There are different ways to define the reference time step: ed <- statespace_ed(x = ind_sel, time = ind_ex$Year, ref_time = ind_ex$Year[1]) ed <- statespace_ed(x = ind_sel, time = ind_ex$Year, ref_time = 1987) ed <- statespace_ed(x = ind_sel, time = ind_ex$Year, ref_time = "1987")