EEMS Map Showing Projections Outside Sample Coordinates

[Genomics-Bhuwan]

Hi everyone,
I ran EEMS and generated the migration rate map for my project. However, I noticed that the map shows projections over Indiana and Ohio, even though I don't have any coordinates or sampling points in those areas. I'm a bit surprised by this and was wondering if it's normal for EEMS to project migration rates outside the provided .coord file.

If anyone could clarify this, I'd really appreciate it. Below is the code I used:

###set working directory.
setwd("E:/Armadillo_Analysis/Final_Armadillo_September_3/EEMS_armadillo_alfredo/Testing/")
##install devtools
library("devtools")
install_github("dipetkov/reemsplots2")
library("reemsplots2")

##install the library
library(terra)
library(tidyterra)
library(tidyverse)
library(ggspatial)

states <- vect("cb_2018_us_state_20m.shp")
states

occ <- read.csv("Dasy_original_GBIF+92_samples.csv")
occ <- occ[occ$countryCode == "US", ]
occ <- vect(occ, crs = "EPSG:4326", geom = c("Longitude", "Latitude"))

occ_shp <- terra::convHull(occ)
##occ_shp <- terra::buffer(occ_shp, 2e4)
occ_shp <- terra::buffer(occ_shp, 16093) # 10 miles in meters
occ_shp <- terra::crop(occ_shp, states)

plot(occ_shp)

studyarea_points <- as.points(as.lines(occ_shp))

write.csv(crds(studyarea_points), "Armadillo.outer", row.names = F)

plot(studyarea_points)

#Vew(as.data.frame(states))
#Filter in only the states we want to see
#st_in <- c("AR", "AL", "TX", "OK", "MO", "IL", "TN", "MS", "LA", "GA", "FL")
#states <- states[states$STUSPS %in% st_in]

Convert to a data frame to extract centroids for labeling

state_df <- as.data.frame(crds(centroids(states))) # Get centroid coordinates
state_df$NAME <- states$NAME # Replace with the actual column from your shapefile

mcmcpath <- paste0(getwd(), "/mcmc")

Define the paths to the MCMC data and the desired output plot location

mcmcpath <-"E:/Armadillo_Analysis/Final_Armadillo_September_3/EEMS_armadillo_alfredo/aaaa/EEMS_Armadillo_not_FEEMS-output/barrier-schemeZ-nIndiv300-nSites3000-EEMS-nDemes200-chain1_res1"
plots <- make_eems_plots(mcmcpath, longlat = TRUE)

#########Plot the map properly

Create the plot with adjustments

Create the plot with adjustments

final_plot <- plots$mrates01 +
scale_fill_whitebox_c(palette = "muted", na.value = "gray10", guide = guide_colorbar(title= "log(m)")) +
geom_spatvector(data = states, inherit.aes = F, fill = NA, linewidth = 0.5) +
geom_spatvector(data = occ_shp, inherit.aes = F, fill = NA) +

Decreasing font size of state names

geom_text(data = state_df, aes(x = x, y = y, label = NAME), size = 3) +

annotation_north_arrow(pad_y = unit(17, "cm")) +
annotation_scale() +
theme_bw() +

Only "Longitude" and "Latitude" in labels

xlab("Longitude") +
ylab("Latitude") +

Increase axis text size (tick labels) and axis labels

theme(
axis.text.x = element_text(size = 14), # Increase X-axis tick label size
axis.text.y = element_text(size = 14), # Increase Y-axis tick label size
axis.title.x = element_text(size = 18, face = "bold"), # Increase X-axis label size
axis.title.y = element_text(size = 18, face = "bold") # Increase Y-axis label size
)

Save the plot as a high-resolution JPEG

ggsave("EEMS_final_heterozygosity_map.jpeg", final_plot, width = 12, height = 8, dpi = 600, device = "jpeg")