library(sf)
library(mapview)
bci<-st_read("BCI.kml")
## Reading layer `BCI' from data source `/home/rstudio/webpages/applied_biogeography/assignment2019/BCI.kml' using driver `LIBKML'
## Simple feature collection with 50 features and 11 fields
## geometry type:  POINT
## dimension:      XY
## bbox:           xmin: -79.85549 ymin: 9.149372 xmax: -79.84728 ymax: 9.153015
## epsg (SRID):    4326
## proj4string:    +proj=longlat +datum=WGS84 +no_defs
mapview(bci)
library(vegan)
library(vegan)
library(tidyverse)
data(BCI)
bci<-data.frame(site=1:50,BCI)
bci[bci==0]<-NA
bci %>% gather(species,count,-1,na.rm=TRUE) -> bci2
DT::datatable(bci2)
vegan::specnumber(BCI)
##   1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18 
##  93  84  90  94 101  85  82  88  90  94  87  84  93  98  93  93  93  89 
##  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36 
## 109 100  99  91  99  95 105  91  99  85  86  97  77  88  86  92  83  92 
##  37  38  39  40  41  42  43  44  45  46  47  48  49  50 
##  88  82  84  80 102  87  86  81  81  86 102  91  91  93
plot(vegan::specaccum(BCI))
## Warning in cor(x > 0): the standard deviation is zero