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Calculate placement of point-wise suitability values on risk quadrant plot

Source: R/calculate_risk_quadrant.R
calculate_risk_quadrant.Rd

This function categorizes the risk of establishment by Lycorma delicatula according to our risk quadrant framework, which is the intersection between predictions made by the global and regional-scale models. It will return which quadrant a suitability value will fall into on an xy-scatter.

Usage

calculate_risk_quadrant(suit.x, suit.y, thresh.x, thresh.y)

Arguments

suit.x

Suitability values comprising the x-axis. Global-scale model is usually placed along the x-axis.

suit.y

Suitability values comprising the y-axis. Regional-scale ensemble model is usually placed along the x-axis.

thresh.x

The threshold for suitability accompanying the x-axis model values.

thresh.y

The threshold for suitability accompanying the y-axis model values.

Value

Returns a data frame. Values will be one of: "extreme", "high", "moderate", or "low". These correspond with our interpretation of the risk quadrant plots we have created:

  • extreme risk = quadrant 4 (upper right)

  • high risk = quadrant 3 (upper left)

  • moderate risk = quadrant 2 (bottom right)

  • low risk = quadrant 1 (bottom left)

Details

#'The function requires the packages 'dplyr' and 'cli'.

Input data formats:

  • param "suit" = matrix of suitability values

  • param "thresh" = numeric

Input suitability data can be created using the function predict_xy_suitability, or extracted from a raster using terra::extract(), as needed.

Examples