marindicators (version 1.0.0)

IVILandings: Calculates the Intrinsic Vulnerability Index of commercial landings

Description

This function calculates the Intrinsic Vulnerability Index (IVI) of the commercial landings for \(j\) areas and \(i\) years.

Usage

IVILandings(land, IVI.table, negative = FALSE, years)

Arguments

land

A dataframe of commercial landings data with columns YEAR, ID, SPECIES and CATCH. YEAR indicates the year the landing was recorded, ID is an area code indicating where the landing was recorded, SPECIES is a numeric code indicating the species landed, and CATCH is the corresponding landed weight.

IVI.table

A dataframe with columns SPECIES and the corresponding IVI (intrinsic vulnerability index). Entries in the SPECIES column should be the unique values of species codes in land (or a subset thereof). Other columns in IVI.table are ignored.

negative

If negative = TRUE, the indicator will be multiplied by -1 so that the expected response is to decrease with increasing fishing pressure. Default is negative = FALSE.

years

A vector of years for which to calculate indicator.

Value

Returns a dataframe with three columns: ID, YEAR, and IVILandings.

If there are no observations in land for spatial scale \(j\) in year \(i\), indicator value is assigned NA.

Details

The weighted Intrinsic Vulnerability Index (IVI) of species in the commercial landings was estimated as: $$IVI = \Sigma(IVI_j * C_j)/\Sigma C_j$$ where the sum is over all species, \(j\). The vulnerability for each species was determined by considering several traits including maximum length, age at first maturity, longevity, von Bertalanffy growth parameter, natural mortality, fecundity, spatial behaviour and geographic range (e.g. species with larger body size, higher longevity, higher age at maturity, and lower growth rates have higher vulnerability indexes and should be less able to sustain high fishing mortality; Cheung et al. 2005). The index values ranges from 1 to 100, with 100 being the most vulnerable. See Appendix 1 from Cheung et al., 2007: http://www.int-res.com/articles/suppl/m333p001_app.pdf

References

Bundy A, Gomez C, Cook AM. 2017. Guidance framework for the selection and evaluation of ecological indicators. Can. Tech. Rep. Fish. Aquat. Sci. 3232: xii + 212 p.

Cheung WWL, Pitcher TJ, Pauly D. 2005. A fuzzy logic expert system to estimate intrinsic extinction vulnerability of marine fishes to fishing. Biol Conserv 124:97<U+2013>111

Cheung WWL, Watson R, Morato T, Pitcher, TJ, Pauly, D. 2007. Intrinsic vulnerability in the global fish catch. Mar Ecol Prog Ser 333: 1 - 12

See Also

Other stability and resistance indicators: CVBiomass, allStability, biomassPerTL, meanMaxAge, meanMaxLength

Examples

# NOT RUN {
# Compile data
data(land)
data(species.info)

# Calculate indicator
IVILandings(land, IVI.table = species.info, negative = TRUE, years = c(2014:2019))
# }