knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
library(DivInsight) data("Colombia")
To subset data for an exact location a pair of longitude/latitude coordinates can be used with subset_by_coordinate_ref()
.
The coordinate_reference
argument will mark the centre of the location and the distance_threshold
will mark the radius of the location in metres.
Below this function is used as an argument value in the clusterise_sites()
function to get clusterised data for two locations in Colombia. The radius of each location is set to 50km.
# clusterise data for a specific location Colombia_coordinate_ref_1 <- clusterise_sites( dataframe = subset_by_coordinate_ref( dataframe = Colombia, coordinate_reference = c(-73.325377, 3.956982), distance_threshold = 50000 ), cluster_min_length = 30 ) # repeat the process with different coordinates Colombia_coordinate_ref_2 <- clusterise_sites( dataframe = subset_by_coordinate_ref( dataframe = Colombia, coordinate_reference = c(-71.889919, 4.470524), distance_threshold = 50000 ), cluster_min_length = 30 )
The diversity over time for both sites can then be plotted.
# scatter plot for reference site 1 plot_sites_scatter_H( clusterised_object = Colombia_coordinate_ref_1, main = "Coordinate Reference Site #1" ) # scatter plot for reference site 2 plot_sites_scatter_H( clusterised_object = Colombia_coordinate_ref_2, main = "Coordinate Reference Site #2" )
The see where these patterns are happening a map can be created.
# create a new map using coordinates from first reference site Colombia_coordinate_ref_map <- map_start( clusterised_object = Colombia_coordinate_ref_1, site_name = "Ref#1", colour = "purple" ) # add to the existing map using information from the second reference site Colombia_coordinate_ref_map <- map_add( existing_map = Colombia_coordinate_ref_map, clusterised_object = Colombia_coordinate_ref_2, site_name = "Ref#2", colour = "darkred" )
The map is ready to be viewed.
# view the interactive map
Colombia_coordinate_ref_map
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