rli: Red List Index.

Description Usage Arguments Details Value References Examples

View source: R/red.R


Calculates the Red List Index (RLI) for a group of species.


rli(spData, tree = NULL, boot = FALSE, runs = 1000)



Either a vector with species assessment categories for a single point in time or a matrix with two points in time in different columns (species x date). Values can be text (EX, EW, RE, CR, EN, VU, NT, DD, LC) or numeric (0 for LC, 1 for NT, 2 for VU, 3 for EN, 4 for CR, 5 for RE/EW/EX).


An hclust or phylo object (used when species are weighted by their unique contribution to phylogenetic or functional diversity).


If TRUE bootstrapping for statistical significance is performed on both values per date and the trend between dates.


Number of runs for bootstrapping


The IUCN Red List Index (RLI) (Butchart et al. 2004, 2007) reflects overall changes in IUCN Red List status over time of a group of taxa. The RLI uses weight scores based on the Red List status of each of the assessed species. These scores range from 0 (Least Concern) to Extinct/Extinct in the Wild (5). Summing these scores across all species and relating them to the worst-case scenario, i.e. all species extinct, gives us an indication of how biodiversity is doing. Each species weight can further be influenced by how much it uniquely contributes to the phylogenetic or functional diversity of the group (Cardoso et al. in prep.). To incorporate Importantly, the RLI is based on true improvements or deteriorations in the status of species, i.e. genuine changes. It excludes category changes resulting from, e.g., new knowledge (Butchart et al. 2007). The RLI approach helps to develop a better understanding of which taxa, regions or ecosystems are declining or improving. Juslen et al. (2016a, b) suggested the use of bootstrapping to search for statistical significance when comparing taxa or for trends in time of the index and this approach is here implemented.


Either a vector (if no two dates are given) or a matrix with the RLI values and, if bootstrap is performed, their confidence limits and significance.


Butchart, S.H.M., Stattersfield, A.J., Bennun, L.A., Shutes, S.M., Akcakaya, H.R., Baillie, J.E.M., Stuart, S.N., Hilton-Taylor, C. & Mace, G.M. (2004) Measuring global trends in the status of biodiversity: Red List Indices for birds. PloS Biology, 2: 2294-2304.

Butchart, S.H.M., Akcakaya, H.R., Chanson, J., Baillie, J.E.M., Collen, B., Quader, S., Turner, W.R., Amin, R., Stuart, S.N. & Hilton-Taylor, C. (2007) Improvements to the Red List index. PloS One, 2: e140.

Juslen, A., Cardoso, P., Kullberg, J., Saari, S. & Kaila, L. (2016a) Trends of extinction risk for Lepidoptera in Finland: the first national Red List Index of butterflies and moths. Insect Conservation and Diversity, 9: 118-123.

Juslen, A., Pykala, J., Kuusela, S., Kaila, L., Kullberg, J., Mattila, J., Muona, J., Saari, S. & Cardoso, P. (2016b) Application of the Red List Index as an indicator of habitat change. Biodiversity and Conservation, 25: 569-585.


rliData <- matrix(c("LC","LC","EN","EN","EX","EX","LC","CR","CR","EX"), ncol = 2, byrow = TRUE)
colnames(rliData) <- c("2000", "2010")
rli(rliData[,1], boot = TRUE)
rli(rliData, boot = TRUE)

red documentation built on May 9, 2018, 1:04 a.m.

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