Calculate overlap of protected area polygons with predicted maxent habitat suitability - polygon

Question

I want to calculate the percentage area of habitat suitability of a species that overlaps with protected area polygons. I do not know the R language very well, but here is what I have so far.
These are the attributes of the area of habitat suitability derived from a maxent prediction:
class : RasterLayer
dimensions : 6480, 8520, 55209600 (nrow, ncol, ncell)
resolution : 0.008333333, 0.008333333 (x, y)
extent : -103, -32, -36, 18 (xmin, xmax, ymin, ymax)
crs : +proj=longlat +ellps=WGS84
of the protected areas:
Simple feature collection with 5667 features and 2 fields (with 8 geometries empty)
geometry type: GEOMETRY
dimension: XY
bbox: xmin: -118.6344 ymin: -59.85538 xmax: -25.29094 ymax: 32.48333
CRS: +proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0
Does someone know a way to calculate the percentage area of habitat suitability that overlaps with protected area polygons?
Sorry, I really do not know so much about how to work with these data. I hope I gave all the relevant information.
I would appreciate any input.

Answer 1

To answer your first question, you should be able to use zonal statistics to calculate the area of potential habitat found in protected areas using the spatialEco package:
zonal.stats(x, y, stats = c("min", "mean", "max"))
#x = Polygon object of class SpatialPolygonsDataFrame
#y = rasterLayer object of class raster
https://www.rdocumentation.org/packages/spatialEco/versions/1.3-0/topics/zonal.stats
Here is a reproducible example from the spatialEco package that first calculates the percentage of pixels in each polygon >= a threshold value and second calculates the sum of pixels in each polygon >= the threshold value used to reclassify the input raster. You might be interested in both avenues for your work.
library(spatialEco)
library(raster)
library(sp)
# here the fxn will calculate the percentage of cells >= 0.5
# percent x >= p function
pct <- function(x, p=0.50, na.rm = FALSE) {
if ( length(x[x >= p]) < 1 ) return(0)
if ( length(x[x >= p]) == length(x) ) return(1)
else return( length(x[x >= p]) / length(x) )
}
# create some example data
p <- raster(nrow=10, ncol=10)
p[] <- runif(ncell(p)) * 10
p <- rasterToPolygons(p, fun=function(x){x > 9})
r <- raster(nrow=100, ncol=100)
r[] <- runif(ncell(r))
plot(r)
plot(p, add=TRUE, lwd=4)
# run zonal statistics using pct functions
z.pct <- zonal.stats(x=p, y=r, stats = "pct")
z.pct
#Alternatively, reclassify the raster based on a threshold
r.c<-reclassify(r, c(-Inf, 0.5, 0, 0.5, Inf, 1)) #all values >0.5 reclassified to 1
plot(r.c)
plot(p, add=TRUE, lwd=4) #add poly to the plot
# run zonal stats and calculate sum of cells in each poly
z.sum <- zonal.stats(x=p, y=r.c, stats = "sum")
z.sum