temp_slr {dilp}R Documentation

Estimate temperature with simple linear regression

Description

temp_slr() will produce estimates of mean annual temperature and standard error using leaf margin analysis.

Usage

temp_slr(
  data,
  regression = "Peppe2018",
  slope = NULL,
  constant = NULL,
  error = NULL
)

Arguments

data

A data frame that must include the columns "morphotype" and "margin". Can be species or site level data.

regression

A string representing one of the following pre-loaded regressions:

  • "Peppe2018" - for global temperature estimates

  • "Peppe2011" - The Americas, Japan, and Oceania

  • "Peppe2011NH" - Peppe 2011 (Northern Hemisphere only)

  • "Miller2006" - North and Central America

  • "WingGreenwood" - East Asia - original leaf margin analysis regression

  • "Wilf1997" - The Americas

slope

Slope, if using a custom regression

constant

Constant, if using a custom regression

error

Standard error, if using a custom regression

Value

A table with MAT estimates for each site

References

Examples

temp_slr(McAbeeExample, regression = "Peppe2011")

[Package dilp version 1.1.0 Index]