whpt | R Documentation |
This function calculates the Whalley Hawkes Paisley Trigg index (WHPT).
whpt(
x,
method = "uk",
type = "ab",
metric = "aspt",
agg = FALSE,
abucl = c(1, 9, 99, 999),
exceptions = NULL,
traceB = FALSE
)
x |
Result of |
method |
The only choice is |
type |
Presence only |
metric |
Possible choices are |
agg |
This option allows the composite family approach. It can be |
abucl |
Log abundance categories. Treshold are set to 1, 9, 99 and 999. |
exceptions |
Taxa that need to be exluded from the calculation. This option can be useful, for instance, to exclude an alien species belonging to an autochthonous family. |
traceB |
If set to |
WHPT is a revision of BMWP and it takes into account the abundances of organisms. The following aggregation is used if agg
is set equal to TRUE
:
Psychomyiidae (inc. Ecnomidae)
Rhyacophilidae (inc. Glossomatidae)
Ancylidae (inc. Acroloxidae)
Gammaridae (inc. Crangonyctidae)
Planariidae (inc. Dugesidae)
Hydrobiidae (inc. Bithyniidae)
whpt()
automatically check for parent-child pairs in the scoring system, see the return section for a definition.
All the information used for WHPT calculation can be retrieved with the function show_scores
.
If traceB
is set to TRUE
a list with the following elements will be returned:
results
Results of whpt()
.
taxa_df
The data.frame
used for the calculation containing the abundance of taxa receiving a score.
abu_df
The data.frame
containing abundance classes for each site.
whpt_df
The data.frame
used for the calculation containing scores for each site.
composite_taxa
Taxa aggregated following the aggregation of the default method or set in agg
.
exceptions
A data.frame
containing the changes made by excluding the taxa included in exceptions
.
parent_child_pairs
For instance in Spanish BMWP both Ferrissia and Planorbidae receive a score.
Abundances of the higher taxonomic level need therefore to be adjusted by subtracting the abundances of the lower taxonomic level.
We thank Carol Fitzpatrick, Richard Chadd, Judy England and Rachel Stubbington for providing us with the most updated WHPT scores and algorithms.
as_biomonitor, aspt, bmwp
data(macro_ex)
data_bio <- as_biomonitor(macro_ex)
data_agr <- aggregate_taxa(data_bio)
whpt(data_agr)
whpt(data_agr, metric = "bmwp")
whpt(data_agr, type = "po", metric = "bmwp")
# take a look to the metrics used for whpt calculation
# only the first 6 rows of each database are shown
lapply(show_scores("whpt", "uk"), head)
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