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Fit an asymptotic model to estimate total species richness beyond the observed sampling effort.

Usage

extrapolate(
  object,
  model = c("michaelis-menten", "lomolino", "asymptotic", "weibull", "logistic", "evt"),
  ...
)

Arguments

object

A spacc object.

model

Character. Model to fit: "michaelis-menten" (default), "lomolino", "asymptotic", "weibull", "logistic", or "evt" (Extreme Value Theory, Borda-de-Agua et al. 2025).

...

Additional arguments passed to stats::nls().

Value

An object of class spacc_fit containing:

asymptote

Estimated total species richness

asymptote_ci

Confidence interval for asymptote

model

Model name

fit

The nls fit object

aic

AIC of the model

References

Lomolino, M.V. (2000). Ecology's most general, yet protean pattern: the species-area relationship. Journal of Biogeography, 27, 17-26.

Flather, C.H. (1996). Fitting species-accumulation functions and assessing regional land use impacts on avian diversity. Journal of Biogeography, 23, 155-168.

Borda-de-Agua, L., Whittaker, R.J., Cardoso, P., et al. (2025). Extreme value theory explains the topography and scaling of the species-area relationship. Nature Communications, 16, 5346.

Examples

# \donttest{
coords <- data.frame(x = runif(50), y = runif(50))
species <- matrix(rbinom(50 * 30, 1, 0.3), nrow = 50)
sac <- spacc(species, coords)
fit <- extrapolate(sac)
print(fit)
# }