Resulting 'best guess' cover values are generated from (in order): recorded
in the field; taxa within environmental pca groups (defined within
env_prcomp); and taxa across all its records. If more than one value is
available, cov_func is used to summarise to a single value.
add_cover(
df,
context = "cell",
env_prcomp,
lucover,
cover_cut_col = "cover_max",
lucover_col = "cover_mid",
small_cov = 0.009,
remove_all_small = TRUE,
fix_1to100 = TRUE,
cov_func = "max"
)Dataframe with context, taxa and cover columns.
Character. Name of columns defining context.
List. Result from call to envClean::env_pca()
Dataframe. Lookup from cover_code to numeric cover values
Character. Name of column in lucover containing values
between 0 and 1 to use for assigning numeric cover values to a cover_code.
This allows the values appearing in the resulting tibble column cover_adj
to be continuous in 0 to 1.
Character. Name of column in lucover containing values
to use for assigning numeric cover values to a cover_code. These do not
have to be between 0 and 1. These values are reflected in the use_cover
value in the resulting tibble.
A small cover value assigned to any record for which there is no available site, pca or taxa cover value.
Logical. If TRUE (default) context(s) where all
taxa are assigned small_cov are removed.
Logical. Any values found in cover field of df that are
above 1 and less than or equal to 100 are divided by 100.
Function to summarise cover values for any context with more than one cover value.
Dataframe with taxa, context and the following 'cover' columns:
cover_adj a best guess proportion cover; use_cover_code the
cover_code values from lucover that correspond to the best guess value;
use_cover the lucover_col column that corresponds to the
best guess value.