predict_d18oc {bayfoxr}

Predict d18O of foram calcite given seawater temperature and seawater d18O.

Description

Predict d18O of foram calcite given seawater temperature and seawater d18O.

Usage

predict_d18oc(seatemp, d18osw, foram = NULL, seasonal_seatemp = FALSE,
  drawsfun = get_draws)

Arguments

seatemp

Numeric or vector of observed sea-surface temperatures (°C).

d18osw

Numeric or vector of observed seawater d18O (‰ VSMOW).

foram

Optional. String or NULL. String indicating the foram species/subspecies to infer for hierarchical models. String must be one of "G. bulloides", "G. ruber", "T. sacculifer", "N. incompta", or "N. pachyderma". NULL indicates that a pooled model is desired.

seasonal_seatemp

Optional boolean indicating whether to use the seasonal sea-surface temperature calibrations. Default is FALSE, i.e. using annual SST calibrations.

drawsfun

Optional function used to get get model parameter draws. Must take arguments for "foram" and "seasonal_seatemp" and return a list with members "alpha", "beta", "tau". This is for debugging and testing. See get_draws.

Details

Four calibration models are available: an "annual pooled" model, a "seasonal pooled" model, an "annual hierarchical" model, and a "seasonal hierarchical" model. This function uses magic to determine which "pooled annual" model is used. Which is the simplest case with potential use for Deep Time reconstructions of nonexant foram species. Giving a valid string for foram will use a hierarchical model, which has foram-specific variability in calibration model parameters. Passing TRUE for seasonal_seatemp will use a model trained on season sea-surface temperatures. See reference paper for further details.

Value

A prediction instance for inferred foraminiferal calcite d18O (‰ VPDB).

See Also

predict_seatemp, predictplot

Examples

# Infer d18Oc for a G. bulloides core top sample using annual hierarchical model.
# The true, d18Oc for this sample is -2.16 (‰ VPDB).
delo_ann <- predict_d18oc(seatemp=28.6, d18osw=0.48, foram="G. bulloides")
head(quantile(delo_ann, probs=c(0.159, 0.5, 0.841)))  # ± 1 standard deviation

# Now using seasonal hierarchical model:
delo_sea <- predict_d18oc(seatemp=28.6, d18osw=0.48, foram="G. bulloides",
                          seasonal_seatemp = TRUE)
head(quantile(delo_sea, probs=c(0.159, 0.5, 0.841)))  # ± 1 standard deviation