add_multiscale_connectivity_penalties: Add multiscale connectivity penalties to a prioritizr problem

In MultiscaleSCP: Multiscale Systematic Conservation Planning Across Nested H3 Grids

Add multiscale connectivity penalties to a prioritizr problem

Description

Adds penalties to a conservation planning problem to account for cross-resolution connectivity between H3 planning units. Connections with larger values are given greater importance when identifying solutions with coordinated selection across resolutions. Connectivity data can be supplied as a matrix, Matrix::dgCMatrix, data frame in Marxan format, or four-dimensional array, following the formats supported by prioritizr::add_connectivity_penalties().

Usage

add_multiscale_connectivity_penalties(
  x,
  penalty,
  zones = diag(prioritizr::number_of_zones(x)),
  data,
  normalize = c("none", "sym")
)

## S4 method for signature 'ANY,ANY,ANY,matrix,character'
add_multiscale_connectivity_penalties(
  x,
  penalty,
  zones = diag(prioritizr::number_of_zones(x)),
  data,
  normalize = c("none", "sym")
)

## S4 method for signature 'ANY,ANY,ANY,Matrix,character'
add_multiscale_connectivity_penalties(
  x,
  penalty,
  zones = diag(prioritizr::number_of_zones(x)),
  data,
  normalize = c("none", "sym")
)

## S4 method for signature 'ANY,ANY,ANY,data.frame,character'
add_multiscale_connectivity_penalties(
  x,
  penalty,
  zones = diag(prioritizr::number_of_zones(x)),
  data,
  normalize = c("none", "sym")
)

## S4 method for signature 'ANY,ANY,ANY,dgCMatrix,character'
add_multiscale_connectivity_penalties(
  x,
  penalty,
  zones = diag(prioritizr::number_of_zones(x)),
  data,
  normalize = c("none", "sym")
)

## S4 method for signature 'ANY,ANY,ANY,array,character'
add_multiscale_connectivity_penalties(
  x,
  penalty,
  zones = diag(prioritizr::number_of_zones(x)),
  data,
  normalize = c("none", "sym")
)

Arguments

x	problem() object.
penalty	numeric value denoting the importance of selecting planning units with strong connectivity between them compared to the main problem objective (e.g., solution cost if x has a minimum set objective set using add_min_set_objective()). Higher penalty values can be used to obtain solutions with a high degree of connectivity, and smaller penalty values can be used to obtain solutions with a small degree of connectivity. Note that negative penalty values can be used to obtain solutions that avoid connectivity.
zones	matrix or Matrix object describing the level of connectivity between different zones. Each row and column corresponds to a different zone in x, and cell values indicate the level of connectivity between each combination of zones. Cell values along the diagonal of the matrix represent the level of connectivity between planning units allocated to the same zone. Cell values must range between 1 and -1, where negative values favor solutions with weak connectivity. Defaults to an identity matrix (i.e., a matrix with ones along the matrix diagonal and zeros elsewhere), so that planning units are only considered to be connected when they are allocated to the same zone. Note that zones is only required when working with multiple zones and data is a matrix or Matrix object. If data is an array or data.frame with data for multiple zones (e.g., using the "zone1" and "zone2" column names), then zones must be NULL.
data	A symmetric connectivity object (matrix, Matrix::dgCMatrix, data frame in Marxan format, or 4D array) describing cross-scale links.
normalize	Either "none" (use data as provided) or "sym" to apply symmetric degree normalization before penalization.

Value

The modified ConservationProblem object.

Functions

• add_multiscale_connectivity_penalties( x = ANY, penalty = ANY, zones = ANY, data = matrix, normalize = character ): matrix method

• add_multiscale_connectivity_penalties( x = ANY, penalty = ANY, zones = ANY, data = Matrix, normalize = character ): Matrix method

• add_multiscale_connectivity_penalties( x = ANY, penalty = ANY, zones = ANY, data = data.frame, normalize = character ): data.frame (Marxan) method

• add_multiscale_connectivity_penalties( x = ANY, penalty = ANY, zones = ANY, data = dgCMatrix, normalize = character ): dgCMatrix method

• add_multiscale_connectivity_penalties( x = ANY, penalty = ANY, zones = ANY, data = array, normalize = character ): array (4D) method

MultiscaleSCP documentation built on Oct. 14, 2026, 5:07 p.m.