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Estimate trophic position using a one source model derived from Post 2002 using a Bayesian framework.

Usage

one_source_model(bp = FALSE)

Arguments

bp

logical value that controls whether informed priors are supplied to the model for \(\delta^{15}\)N baseline. Default is FALSE meaning the model will use uninformed priors, however, the supplied data.frame needs values for \(\delta^{15}\)N baseline (n1).

Value

returns model structure for one source model to be used in a brms() call.

Details

$$\delta^{15}N = \delta^{15} N_1 + \Delta N \times (tp - \lambda_1)$$

\(\delta^{15}\)N are values from the consumer, \(\delta^{15} N_1\) is mean \(\delta^{15}\)N values of baseline 1, \(\Delta\)N is the trophic discrimination factor for N (i.e., dn mean of 3.4), \(tp\) is trophic position, and \(\lambda_1\) is the trophic level of baselines which are often a primary consumer (e.g., 2).

The data supplied to brms() needs to have the following variables d15n, n1, and l1 (\(\lambda\)) which is usually 2.

See also

Examples

one_source_model()
#> d15n ~ n1 + dn * (tp - l1) 
#> dn ~ 1
#> tp ~ 1