Multiple Protected Connected (ProtConn)

Estimate Protected Connected (ProtConn) indicator and fractions for multiple regions.

MK_ProtConnMult(
  nodes,
  regions,
  area_unit = "m2",
  distance = list(type = "centroid", resistance = NULL),
  distance_thresholds,
  probability,
  transboundary = NULL,
  transboundary_type = "nodes",
  protconn_bound = FALSE,
  geom_simplify = FALSE,
  delta = FALSE,
  CI = "all",
  plot = FALSE,
  write = NULL,
  intern = TRUE,
  parallel = NULL
)

Arguments

nodes	object of class sf, sfc, sfg or SpatialPolygons. The file must have a projected coordinate system.
regions	object of class sf, sfc, sfg or SpatialPolygons. The file must have a projected coordinate system.
area_unit	character. Attribute area units. You can set an area unit, "Makurhini::unit_covert()" compatible unit ("m2", "Dam2, "km2", "ha", "inch2", "foot2", "yard2", "mile2"). Default equal to hectares "m2".
distance	list. See distancefile. Example, list(type= "centroid", resistance = NULL).
distance_thresholds	numeric. Distance or distances thresholds to establish connections (meters). For example, one distance: distance_threshold = 30000; two or more specific distances: distance_threshold = c(30000, 50000); sequence distances: distance_threshold = seq(10000,100000, 10000).
probability	numeric. Connection probability to the selected distance threshold, e.g., 0.5 that is 50 percentage of probability connection. numeric. If probability = NULL, then it will be the inverse of the mean dispersal distance for the species (1/α; Hanski and Ovaskainen 2000).
transboundary	numeric. Buffer to select polygons in a second round, their attribute value = 0, see Saura et al. 2017.
transboundary_type	character. Two options: "nodes" or "region". If it is "nodes" the transboundary is built from the limits of the nodes present in the region (default), if "region" is selected the transboundary is built from the limits of the region.
protconn_bound	logical. If TRUE then the fractions ProtUnConn[design] and ProtConn[bound] will be estimated.
geom_simplify	logical. Slightly simplify the region and nodes geometries.
delta	logical. Estimate the contribution of each node to the ProtConn value in the regions.
CI	character. A character vector representing the type of confidence intervals that will be estimated. The value should be any subset of the values c("norm","basic", "stud", "perc", "bca") or "all" which will compute all five types of intervals (see, boot.ci)
plot	logical. Plot the main ProtConn indicators and fractions with their standard deviation, default = FALSE.
write	character. Output folder including the output file name without extension, e.g., "C:/ProtConn/Protfiles".
intern	logical. Show the progress of the process, default = TRUE. Sometimes the advance process does not reach 100 percent when operations are carried out very quickly.
parallel	numeric. Specify the number of cores to use for parallel processing, default = NULL. Parallelize the function using furrr package and multiprocess plan.

Value

Table with the following ProtConn values: ECA, Prot, ProtConn, ProtUnconn, RelConn, ProtUnConn[design], ProtConn[bound], ProtConn[Prot], ProtConn[Within], ProtConn[Contig], ProtConn[Trans], ProtConn[Unprot], ProtConn[Within][land], ProtConn[Contig][land], ProtConn[Unprot][land], ProtConn[Trans][land]

*Each indicator is accompanied by six dispersion statistics: standard deviation, standard error and four confidence intervals obtained with a bootstrap-type resampling (Carpenter & Bithell 2000; see, ProtConnStat())

*If plot is not TRUE a list is returned with the ProtConn table and a plots.

References

Saura, S., Bastin, L., Battistella, L., Mandrici, A., & Dubois, G. (2017). Protected areas in the world’s ecoregions: How well connected are they? Ecological Indicators, 76, 144–158. Saura, S., Bertzky, B., Bastin, L., Battistella, L., Mandrici, A., & Dubois, G. (2018). Protected area connectivity: Shortfalls in global targets and country-level priorities. Biological Conservation, 219(October 2017), 53–67.

Examples

if (FALSE) {
library(Makurhini)
library(sf)
data("Protected_areas", package = "Makurhini")
plot(Protected_areas, col="green")

data("regions", package = "Makurhini")
plot(regions, col=c("blue", "red", "green"))

test <- MK_ProtConnMult(nodes = Protected_areas,
                        regions = regions,
                        area_unit = "ha",
                        distance = list(type= "centroid"),
                        distance_thresholds = c(10000, 50000),
                        probability = 0.5, transboundary = 50000,
                        plot = TRUE, write = NULL,
                        parallel = NULL, intern = TRUE)
test
}