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Sensitivity analysis across maps of habitat connectivity

Source: R/sean.R
sean.Rd

This function performs a sensitivity analysis across different values of habitat connectivity for each location in a map. For each combination of selected parameters, an index of habitat connectivity is calculated. sensitivity_analysis() is a wrapper around sean() function.

  • msean() is a wrapper around sean() function. It has additional argument to specify maps which are calculated using connectivity() function. The maps are essentially the risk network.

Usage

sean(
  rast,
  global = TRUE,
  geoscale = NULL,
  agg_methods = c("sum", "mean"),
  dist_method = "geodesic",
  link_threshold = 0,
  hd_threshold = 0,
  res = reso(),
  inv_pl = inv_powerlaw(NULL, betas = c(0.5, 1, 1.5), mets = c("betweeness",
    "NODE_STRENGTH", "Sum_of_nearest_neighbors", "eigenVector_centrAlitY"), we = c(50,
    15, 15, 20), linkcutoff = -1),
  neg_exp = neg_expo(NULL, gammas = c(0.05, 1, 0.2, 0.3), mets = c("betweeness",
    "NODE_STRENGTH", "Sum_of_nearest_neighbors", "eigenVector_centrAlitY"), we = c(50,
    15, 15, 20), linkcutoff = -1)
)

msean(
  rast,
  global = TRUE,
  geoscale = NULL,
  res = reso(),
  ...,
  outdir = tempdir()
)

Arguments

rast

Raster object which will be used in analysis.

global

Logical. TRUE if global analysis, FALSE otherwise. Default is TRUE

geoscale

Numeric vector. Geographical coordinates in the form of c(Xmin, Xmax, Ymin, Ymax) which EPSG:4326 in coordinate reference system. If geoscale is NuLL, the extent is extracted from rast(SpatRaster) using terra::ext().

agg_methods

Character. One or both the values - SUM, MEAN. Aggregation strategy for scaling the input raster to the desired resolution.

dist_method

Character. The method to calculate the distance matrix.

link_threshold

Numeric. A threshold value for link weight. All link weights that are below this threshold will be replaced with zero for the connectivity analysis. Link weights represent the relative likelihood of pathogen, pest, or invasive species movement between a pair of host locations, which is calculated using gravity models based on host density (or availability) and dispersal kernels.

hd_threshold

Numeric. A threshold value for host density. All locations with a host density below the selected threshold will be excluded from the connectivity analysis, which focuses the analysis on the most important locations. The values for the host density threshold can range between 0 and 1; if value is 1, all locations will be excluded from the analysis and 0 will include all locations in the analysis. Selecting a threshold for host density requires at least knowing what is the maximum value in the host density map to avoid excluding all locations in the analysis. if value is 1, all locations will be excluded from the analysis and 0 will include all locations in the analysis. Selecting a threshold for host density requires at least knowing what is the maximum value in the host density map to avoid excluding all locations in the analysis.

res

Numeric. Resolution of the raster. Default is reso().

inv_pl

List. A named list of parameters for inverse power law. See details.

neg_exp

List. A named list of parameters for inverse negative exponential. See details. All locations with a host density below the selected threshold will be excluded from the connectivity analysis, which focuses the analysis on the most important locations. The values for the host density threshold can range between 0 and 1;

...

arguments passed to sean()

outdir

Character. Output directory for saving raster in TIFF format. Default is tempdir().

Value

GeoRasters.

GeoNetwork.

Details

When global = TRUE, geoscale is ignored and global_scales() is used by default.

The functions sean() and msean() perform the same sensitivity analysis, but they differ in their return value. The return value of msean() is GeoNetwork, which contains the result from applying the connectivity() function on the habitat connectivity indexes. Essentially, the risk maps.

If neither the inverse power law nor the negative exponential dispersal kernel is specified, the function will return an error.

In msean(), three spatRasters are produced with the following values. For each location in the area of interest, the mean in habitat connectivity across selected parameters is calculated. For each location in the area of interest, the variance in habitat connectivity across selected parameters is calculated. For each location in the area of interest, the difference between the rank of habitat connectivity and the rank of host density is calculated. By default, each of these spatRasters is plotted for visualization.

References

Yanru Xing, John F Hernandez Nopsa, Kelsey F Andersen, Jorge L Andrade-Piedra, Fenton D Beed, Guy Blomme, Mónica Carvajal-Yepes, Danny L Coyne, Wilmer J Cuellar, Gregory A Forbes, Jan F Kreuze, Jürgen Kroschel, P Lava Kumar, James P Legg, Monica Parker, Elmar Schulte-Geldermann, Kalpana Sharma, Karen A Garrett, Global Cropland .connectivity: A Risk Factor for Invasion and Saturation by Emerging Pathogens and Pests, BioScience, Volume 70, Issue 9, September 2020, Pages 744–758, doi:10.1093/biosci/biaa067

Hijmans R (2023). terra: Spatial Data Analysis. R package version 1.7-46, https://CRAN.R-project.org/package=terra

See also

Uses connectivity()

Uses msean() inv_powerlaw() neg_expo()

Examples

# \donttest{
avocado <- cropharvest_rast("avocado", "monfreda")

# global
ri <- sean(avocado) # returns a list of GeoRasters
mri <- msean(rast = avocado) # returns GeoNetwork object

# non-global
# geoscale is a vector of xmin, xmax, ymin, ymax

# returns GeoRasters object
ri <- sean(avocado, global = FALSE, geoscale = c(-115, -75, 5, 32))
ri

# returns GeoNetwork object
mri <- msean(rast = avocado, global = FALSE, geoscale = c(-115, -75, 5, 32))
mri
# }