1 Data
1.1 Climate data
source("code/data_chelsa.R")
df_chelsa## # A tibble: 8 × 4
## site mat tap vpd
## <chr> <dbl> <dbl> <dbl>
## 1 SJ 14.6 650. 971
## 2 DV 8.05 432. 1131.
## 3 AT 19.8 931. 1810.
## 4 ST 10.7 1118. 839.
## 5 NY 12.2 1216. 1319.
## 6 DT 10.3 984. 1211.
## 7 TP 22.1 1355. 1365
## 8 HT 20.4 1343. 1525.Climatologies.
source("code/data_terraclim.R")
df_terraclim## # A tibble: 7 × 3
## site mat tap
## <chr> <dbl> <dbl>
## 1 AT 19.4 842.
## 2 DV 9.25 424
## 3 ST 10.9 1011
## 4 HT 21.3 1249.
## 5 NY 12.3 1198.
## 6 DT 10.2 869.
## 7 TP 22.6 1298Annual summaries.
source("code/data_terraclim_annual.R")
df_terraclim_annual## # A tibble: 35 × 4
## site mat tap year
## <chr> <dbl> <dbl> <int>
## 1 AT 20.0 882 2018
## 2 DV 9.92 364. 2018
## 3 ST 11.5 955. 2018
## 4 HT 22.0 1281. 2018
## 5 NY 13.1 1720. 2018
## 6 DT 10.8 1063. 2018
## 7 TP 23.4 1579. 2018
## 8 AT 20.1 783. 2019
## 9 DV 9.61 342. 2019
## 10 ST 11.6 812. 2019
## # ℹ 25 more rows1.2 NAB data
Read in data using tidynab package.
source("code/data_nab_read.R")Focus on seven cities. * Exceptions: Denver pollen data are from Colorado Springs; Austin pollen data are from Georgetown; Detroit pollen data are from Sylvania.
source("code/data_nab_meta.R")
p_pollen_map
source("code/data_nab_avail.R")
p_nab_avail
View pollen phenology in study sites.
source("code/data_nab_pheno.R")
p_nab_calen
source("code/data_nab_window.R")
p_flower_window
1.3 Plant location data
Read in data previously processed with batchplanet package.
source("code/data_occ_tree_read.R")Find family names from genus names. This step needs supervision.
source("code/data_occ_tree_taxa.R")Map relative position of tree inventory and nab station.
source("code/data_occ_map.R")
p_nab_plant_map
Calculate distance from plants to NAB stations in the unit of km.
source("code/data_occ_dist.R")
df_distance## # A tibble: 7 × 7
## site midlon midlat sitelon sitelat sitename distance
## <chr> <dbl> <dbl> <dbl> <dbl> <fct> <dbl>
## 1 AT -97.7 30.3 -97.7 30.6 Austin 41.0
## 2 DT -83.1 42.4 -83.7 41.7 Detroit 90.7
## 3 DV -105. 39.7 -105. 38.9 Denver 96.5
## 4 HT -95.4 29.7 -95.4 29.7 Houston 3.92
## 5 NY -73.9 40.7 -74.0 40.8 New York 10.6
## 6 ST -122. 47.6 -122. 47.7 Seattle 6.91
## 7 TP -82.4 28.1 -82.4 28.1 Tampa 3.65Prepare street map as basemap. Street shapefiles for major cities manually downloaded from https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/CUWWYJ. Boeing, Geoff, 2017, “U.S. Street Network Shapefiles, Node/Edge Lists, and GraphML Files”, https://doi.org/10.7910/DVN/CUWWYJ, Harvard Dataverse, V2
source("code/data_occ_road_read.R")Map plant occurrence in a city.
source("code/data_occ_road_map.R")
p_plant_map
