From a72dfbf83cac22e6eabfc339807ea9a1e1f36f56 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?K=C3=B6nig?= <ye87zine@usr.idiv.de>
Date: Thu, 9 Jan 2025 12:41:59 +0100
Subject: [PATCH] filtered duplicate occurrences, auto bandwidth in spatial kde
---
R/03_01_presence_preparation.R | 8 ++++++--
R/03_02_absence_preparation.R | 29 +++++++++++++++--------------
2 files changed, 21 insertions(+), 16 deletions(-)
diff --git a/R/03_01_presence_preparation.R b/R/03_01_presence_preparation.R
index 9fb6ee3..8d3fce3 100644
--- a/R/03_01_presence_preparation.R
+++ b/R/03_01_presence_preparation.R
@@ -73,7 +73,11 @@ raster_data = terra::project(raster_data, proj_string)
occs_final = st_transform(occs_final, proj_string)
env_data = extract(raster_data, vect(occs_final), ID = F)
-# Save occurrences
+# Merge data + final processing
occs_final = bind_cols(occs_final, env_data) %>%
- drop_na()
+ drop_na() %>% # Remove records with NA env vars
+ group_by(species) %>%
+ distinct() # Remove duplicate records
+
+# Save occurrences
save(occs_final, file = "data/r_objects/occs_final.RData")
diff --git a/R/03_02_absence_preparation.R b/R/03_02_absence_preparation.R
index 951dded..2390512 100644
--- a/R/03_02_absence_preparation.R
+++ b/R/03_02_absence_preparation.R
@@ -85,8 +85,7 @@ model_data = furrr::future_walk(
# Define spatial KDE
ref = st_bbox(sampling_region)[c(1,3,2,4)]
- min_extent = min(ref[2]-ref[1], ref[4]-ref[3])
- spatial_kde = spatialEco::sf.kde(occs_spec, bw = min_extent/2, res = 10000, ref = ref, standardize = T, scale.factor = 1) %>%
+ spatial_kde = spatialEco::sf.kde(occs_spec, res = 10000, ref = ref, standardize = T, scale.factor = 1) %>%
crop(sampling_region, mask = T, touches = F)
# Define reverse niche
@@ -110,7 +109,7 @@ model_data = furrr::future_walk(
if(length(sample_points) == 0){
next
}
-
+
samples_required = nrow(occs_spec) - nrow(abs_spec)
if(length(sample_points) > samples_required){
sample_points = sample(sample_points, samples_required)
@@ -136,17 +135,19 @@ model_data = furrr::future_walk(
dplyr::mutate(present = 1) %>%
bind_rows(abs_spec)
- # ggplot() +
- # ggtitle(species) +
- # geom_sf(data = st_crop(sa_polygon, ref), fill = "#756445") +
- # tidyterra::geom_spatraster(data = abs_prob) +
- # scale_fill_gradient(low="darkblue", high="green", na.value=NA, name = "Absence sampling probability") +
- # geom_sf(data = range_spec, alpha = 0, color = "black") +
- # geom_sf(data = pa_spec, aes(color = as.factor(present)), size = 0.7) +
- # scale_color_discrete(name = "Presence") +
- # theme_minimal()
- #
- # ggsave(paste0(species, ".pdf"), path = "plots/pa_sampling", device = "pdf", scale = 2)
+ ggplot() +
+ ggtitle(species) +
+ geom_sf(data = st_crop(sa_polygon, ref), fill = "#756445") +
+ tidyterra::geom_spatraster(data = abs_prob) +
+ scale_fill_gradient(low="darkblue", high="green", na.value=NA, name = "Absence sampling probability") +
+ geom_sf(data = range_spec, alpha = 0, color = "black") +
+ geom_sf(data = pa_spec, aes(color = as.factor(present)), size = 0.7) +
+ scale_color_discrete(name = "Presence") +
+ theme_minimal()
+
+ try({
+ ggsave(paste0(species, ".pdf"), path = "plots/pa_sampling", device = "pdf", scale = 2)
+ })
# Define cross-validation folds
folds = tryCatch({
--
GitLab