Use Chao et al. 2014 approach for rarefaction and extrapolation

ISAR_DATA/alpha_Sn_frag.csv

@@ -0,0 +1,12 @@
+"";"Site";"m";"order";"qD";"qD.LCL";"qD.UCL";"SC";"SC.LCL";"SC.UCL"
+"1";1;340;0;20,903;10,512;31,295;0,982;0,953;1,011
+"2";2;340;0;25,065;16,635;33,495;0,963;0,936;0,991
+"3";3;340;0;23,861;19,291;28,43;0,981;0,965;0,997
+"4";4;340;0;16,88;9,697;24,063;0,987;0,964;1,01
+"5";5;340;0;15,8315;7,58;24,0835;0,9965;0,98;1,014
+"6";6;340;0;16,4325;9,805;23,0605;0,9805;0,9595;1,0015
+"7";7;340;0;24,8795;19,673;30,0855;0,9845;0,9685;1,0015
+"8";8;340;0;27,4225;21,456;33,3895;0,9715;0,9465;0,9965
+"9";9;340;0;31,5666666666667;23,2226666666667;39,911;0,971;0,940666666666667;1,00033333333333
+"10";10;340;0;30,664;19,0633333333333;42,2653333333333;0,958;0,917;0,998666666666667
+"11";11;340;0;21,6973333333333;16,6803333333333;26,7133333333333;0,975;0,958;0,992666666666667

ISAR_DATA/gamma_frag.csv

@@ -0,0 +1,12 @@
+"";"m";"order";"qD";"qD.LCL";"qD.UCL";"SC";"SC.LCL";"SC.UCL";"Site"
+"V1.6";340;0;20,903;9,111;32,696;0,982;0,951;1,013;1
+"V2.6";340;0;25,065;18,73;31,4;0,963;0,939;0,987;2
+"V3.6";340;0;23,861;19,388;28,334;0,981;0,966;0,997;3
+"V4.6";340;0;16,88;10,612;23,147;0,987;0,967;1,008;4
+"V5.6";340;0;22,361;16,46;28,261;0,984;0,962;1,007;5
+"V6.3";340;0;17,225;14,321;20,128;0,986;0,978;0,993;6
+"V7.3";340;0;29,619;25,932;33,305;0,968;0,959;0,977;7
+"V8.3";340;0;29,532;25,894;33,17;0,967;0,959;0,975;8
+"V9.3";340;0;34,35;31,431;37,27;0,962;0,954;0,969;9
+"V10.3";340;0;34,669;30,829;38,509;0,959;0,949;0,97;10
+"V11.3";340;0;24,995;22,27;27,721;0,969;0,962;0,976;11

R_scripts/2_calculate_Sn_values.R

@@ -6,7 +6,17 @@
 # load transect level data and iNEXT
 
 library(iNEXT)
-frag_abund <- read_csv("Desktop/ISAR_DATA/datasets/forest_fragments_data.csv")
+library(tidyverse)
+
+# please set all path relative to the GitHub repo folder 
+# to do that please do the following in RStudio:
+# Menu Session --> Set working directory --> To project directory
+work_dir <- getwd()
+
+frag_abund <- read_csv("ISAR_DATA/datasets/forest_fragments_data.csv")
+
+# The file is called forest fragments, but the species names are really familier to me.
+# Apparently this is data from my project in Israel. Is this correct???
 
 # Transpose data to fit iNEXT data format requirement
 Site_names <- frag_abund$Site
@@ -15,10 +25,19 @@ frag_abund$Site <- NULL
 t_frag_abund<- t(frag_abund)
 t_frag_abund <- as.data.frame(t_frag_abund)
 
+# Implement approach by Chao et al. 2014
+n_sites <- rowSums(frag_abund)
+
+r <- 2
+
+max_n <- max(n_sites)
+min_n_r <- min(r * n_sites)
+n <- max(max_n, min_n_r)
+# --------------------
 
 # Get average N values where Sn will be interpolated or extrapolated 
 #from local rarefaction curves (one curve per transect per fragment)
-n <- round(mean(rowSums(frag_abund)))
+#n <- round(mean(rowSums(frag_abund)))
 
 m <- c(10,20,n)
 
@@ -43,11 +62,13 @@ average_Sn_alpha <- ext_dat_a %>%
   summarise_all(mean)
 
 # Save iNEXT Sn estimates and calculate average Sn values per fragment
-write.csv2(average_Sn_alpha, "/Users/leanagooriah/desktop/ISAR_DATA/alpha_Sn_frag.csv")
+outfile <- paste(work_dir, "/ISAR_DATA/alpha_Sn_frag.csv", sep = "") 
+write.csv2(average_Sn_alpha, outfile)
 
 
 ###### GAMMA SN ESTIMATES #####
-frag_abund <- read_csv("Desktop/ISAR_DATA/datasets/forest_fragments_data.csv")
+
+frag_abund <- read_csv("ISAR_DATA/datasets/forest_fragments_data.csv")
 
 # Calculate summed up abundance 
 frag_sum <- frag_abund %>%
@@ -73,6 +94,8 @@ ext_dat_g <- subset(ext_dat_g, m == n)
 ext_dat_g$method <- NULL
 ext_dat_g$Site <- Site_names
 # Save iNEXT gamma Sn estimates 
-write.csv2(ext_dat_g, "/Users/leanagooriah/desktop/ISAR_DATA/gamma_frag.csv")
+
+outfile <- paste(work_dir, "/ISAR_DATA/gamma_frag.csv", sep = "") 
+write.csv2(ext_dat_g, outfile)