Sequential extrapolation estimate

sequentialExtrapolate uses rates of decline from getDeclineStats and generates a sequence of estimates at regular time-steps. Useful for generating a sequence for plotting graphs.

Usage

sequentialExtrapolate(A.t1, year.t1, nYears, ARD = NA, PRD = NA, ARC = NA)

Arguments

A.t1

Area at time t1

year.t1

Year of time t1

nYears

Number of years since t1 for prediction. Use negative values for backcasting

ARD

Absolute rate of decline

PRD

Proportional rate of decline

ARC

Annual rate of change

Value

A dataframe with the forecast year, and a combination of:

• Sequence of values as extrapolated with absolute rate of decline (ARD)

• Sequence of values as extrapolated with proportional rate of decline (PRD)

• Sequence of values as extrapolated with annual rate of change (ARC)

References

IUCN 2024. Guidelines for the application of IUCN Red List of Ecosystems Categories and Criteria, Version 2.0. Keith, D.A., Ferrer-Paris, J.R., Ghoraba, S.M.M., Henriksen, S., Monyeki, M., Murray, N.J., Nicholson, E., Rowland, J., Skowno, A., Slingsby, J.A., Storeng, A.B., Valderrábano, M. & Zager, I. (Eds.) Gland, Switzerland: IUCN. ix + 94pp. https://doi.org/10.2305/CJDF9122

See also

Other change_functions: extrapolateEstimate(), futureAreaEstimate()

Author

Calvin Lee calvinkflee@gmail.com

Examples

a.r1 <- 23.55
a.r2 <- 15.79
decline.stats <- getDeclineStats(a.r1, a.r2, year.t1 = 1990, year.t2 = 2012,
                                 methods = 'PRD')
a.2040.PRD.seq <- sequentialExtrapolate(a.r1, a.r2, year.t1 = 1990, nYears = 50,
                                        PRD = decline.stats$PRD)