bioturb: Bioturbate time series using diffusion model from Guinasso...

In astrochron: A Computational Tool for Astrochronology

Bioturbate time series using diffusion model from Guinasso and Schinck (1975), as in Liu et al. (2021)

Description

'bioturb' is a function for simulating the bioturbed time series when bioturbation is modeled as a diffusive process. It implements the methodology outlined in Liu et al. (2021), which builds on the approaches of (Guinasso and Schink, 1975), Goreau (1977), and Goreau (1980). Given the bioturbation parameters, an impulse response function is first calculated using function 'impulseResponse'. This function is then convolved with the input time series (true signal) to output the bioturbed time series. Note that the input true signal 'dat' and impulse response function are interpolated to the same resolution before convolution.

Usage

bioturb(dat, G, ML, v, output=1, genplot=TRUE, verbose=TRUE)

Arguments

dat	Stratigraphic series to be bioturbated. First column should be age (kyr), second column should be data value.
G	Control parameter in Guinasso and Schinck, 1975. G = D/ML/v
ML	Mix layer depth (cm)
v	Sedimentation rate (cm/kyr)
output	Which results would you like to return to the console? (0) no output; (1) return bioturbated series; (2) return impulse response
genplot	Generate summary plots? (T or F)
verbose	Verbose output? (T or F)

References

Guinasso, N.L. and Schinck, D.R., 1975, Quantitative estimates of biological mixing rates in abyssal sediments, J. Geophys. Res., 80, 3032-3043.

Goreau, T.J., 1977, Quantitative effects of sediment mixing on stratigraphy and biogeochemistry: a signal theory approach, Nature, 256, 730-732.

Goreau, T.J., 1980, Frequency sensitivity of the deep-sea climatic record, Nature, 287, 620-622.

Liu, H., Meyers, S.R., and Marcott, S.A., 2021, Unmixing dee-sea paleoclimate records: A study on bioturbation effects through convolution and deconvolution, Earth and Planetary Science Letters, 564, 116883.

Examples

# as a test series, use the three dominant precession terms from Berger et al. (1992)
ex1=cycles()

# mix it
res1 <- bioturb(ex1, G=4, ML=10, v=1, genplot = TRUE)

# un-mix it
res2=unbioturb(res1, G=4, ML=10, v=1, genplot = TRUE)

pl()
plot(ex1,type="l",main="black=signal, blue=bioturbated, red=unbioturbated",lwd=3)
lines(res2,col="red")
lines(res1,col="blue")

astrochron documentation built on Sept. 30, 2024, 9:14 a.m.