cat_criterion_c: Categorize taxa according to IUCN criterion C

In gdauby/ConR: Computation of Parameters Used in Preliminary Assessment of Species Conservation Status

Categorize taxa according to IUCN criterion C

Description

Provide the consensus IUCN category based on the sub-criteria of IUCN criterion C (C1, C2ai, C2aii and C2b) and the thresholds recommended by IUCN.

Usage

cat_criterion_c(
  C1_df = NULL,
  C2_df = NULL,
  C.threshold = c(10000, 2500, 250),
  C1.threshold = c(10, 20, 25),
  C2ai.threshold = c(1000, 250, 50),
  C2aii.threshold = c(90, 95, 100),
  mag.fluct = 10,
  high.alter = 80,
  all.cats = TRUE
)

Arguments

C1_df	data frame with the parameters necessary to assess IUCN sub-criterion C1.
C2_df	data frame with the parameters necessary to assess IUCN sub-criteria C2.
C.threshold	numeric vector with the criterion C thresholds to define small population sizes (e.g. number of mature individuals). Default values are the thresholds recommended by the IUCN.
C1.threshold	numeric vector with the C1 thresholds to convert continuing decline estimates into categories. Default is the thresholds recommended by IUCN.
C2ai.threshold	numeric vector with the C2ai thresholds to assess the number of mature individuals in each subpopulation. Default is the thresholds recommended by IUCN.
C2aii.threshold	numeric vector with the C2aii thresholds to assess the proportion of mature individuals in one subpopulation. Default is the thresholds recommended by IUCN.
mag.fluct	numerical. Threshold of mean order of magnitude of the differences between population minima and maxima to classify populations with extreme fluctuations. Default to 10 as recommended by IUCN (2019).
high.alter	numerical. Threshold of proportion of changes that are followed by a change in the opposite direction. Default to 80%, but currently not implemented
all.cats	logical. Should the categories from all criteria be returned and not just the consensus categories? Default to TRUE.

Details

By default, the function provides the consensus category, following the recommendations of IUCN (2019) that states "Only the criteria for the highest category of threat that the taxon qualifies for should be listed". Therefore, the consensus category is the highest category of threat among the sub-criteria evaluated.

The function assumes that the order of the values in C1_df and C2_df are from the same taxa (i.e. first element from C1_df and C2_df is always the same species i). Therefore, the order of the estimates of population size and continuing decline for each sub-criterion must be the same.

Value

A list containing a vector of the consensus category from all sub-criteria evaluated for each taxon (ranks_C) and the sub-criteria used to obtain the consensus category (cat_codes). If all.cats == TRUE the function also returns a data frame containing the categories classified by each sub-criteria individually (all.cats).

Author(s)

Renato A. Ferreira de Lima & Gilles Dauby

References

IUCN 2019. Guidelines for Using the IUCN Red List Categories and Criteria. Version 14. Standards and Petitions Committee. Downloadable from: http://www.iucnredlist.org/documents/RedListGuidelines.pdf.

gdauby/ConR documentation built on Jan. 30, 2024, 11:10 p.m.