zdealveindy

	T1_1	T1_2	T1_3	T1_4	T1_5	T1_6	T2_1	T2_2	T2_3	T2_4	T2_5	T2_6	T2_7	T2_8	T2_9	T2_10	T2_11	T2_12	T2_13
S01	99	100	100	98	100	100	100	100	100	100	93	100	100	100	100	99	100	97	100
S02	100	100	100	99	100	100	100	100	100	100	100	100	100	100	99	100	100	100	27
S03	100	100	100	100	100	100	100	100	100	100	100	100	100	100	100	100	100	100	0
S04	100	100	100	99	100	100	100	100	99	92	100	96	100	100	100	100	100	100	0
S05	100	100	100	98	100	100	100	96	97	93	100	100	98	98	100	90	100	98	0
S06	100	100	100	100	100	100	100	99	99	99	100	97	100	100	99	80	98	96	0
S07	100	100	100	100	100	100	100	100	100	100	100	98	100	100	100	0	100	100	38
S08	100	100	100	98	100	100	99	100	100	57	100	100	100	100	100	62	100	97	0
S09	100	100	99	0	100	100	100	100	100	100	100	100	100	100	100	100	100	100	12

zdealveindy

	CK_1	CK_2	CK_3	CK_4	CK_5	CK_6	DA_1	DA_2	DA_3	DA_4	DA_5	DA_6	DA_7	DA_8	DA_9	DA_10	DA_11	DA_12	DA_13
b09b01019	99	100	100	98	100	100	100	100	100	100	93	100	100	100	100	99	100	97	100
b07605051	100	100	100	99	100	100	100	100	100	100	100	100	100	100	99	100	100	100	27
b07208023	100	100	100	100	100	100	100	100	100	100	100	100	100	100	100	100	100	100	0
b06608068	100	100	100	99	100	100	100	100	99	92	100	96	100	100	100	100	100	100	0
b07b01004	100	100	100	98	100	100	100	96	97	93	100	100	98	98	100	90	100	98	0
b09b01023	100	100	100	100	100	100	100	99	99	99	100	97	100	100	99	80	98	96	0
b09b01013	100	100	100	100	100	100	100	100	100	100	100	98	100	100	100	0	100	100	38
b09b01007	100	100	100	98	100	100	99	100	100	57	100	100	100	100	100	62	100	97	0
b08b01012	100	100	99	0	100	100	100	100	100	100	100	100	100	100	100	100	100	100	12

zdealveindy

scale_override <- function(which, scale) {
  if(!is.numeric(which) || (length(which) != 1) || (which %% 1 != 0)) {
    stop("which must be an integer of length 1")
  }
  
  if(is.null(scale$aesthetics) || !any(c("x", "y") %in% scale$aesthetics)) {
    stop("scale must be an x or y position scale")
  }
  
  structure(list(which = which, scale = scale), class = "scale_override")

zdealveindy

# Individual examples
# 1) Both w1 and w2 similarly related to y
set.seed (1234)
# Generate two random variables N(0,1)
x1 <- rnorm (100, 0, 1)
x2 <- rnorm (100, 0, 1)
X <- cbind (x1, x2)
# Generate correlation matrix to make variables correlated at r = 0.8
R <- matrix (c(sqrt (.8), sqrt (.2), sqrt (0.2), sqrt (.8)), ncol = 2)
W <- X%*%R

zdealveindy

# Hellinger distance

library (vegan)
png (width = 6, height = 6, units = 'in', res = 300)
par (mar = c(5,5,2,2))
plot (0:1, 0:1, xlab = list ('Species 1', cex = 1.5), ylab = list ('Species 2', cex = 1.5), axes = F, xlim = c(0, 1.3), ylim = c(0,1.3), type = 'n')
par (xpd = NA)
arrows (x0 = 0, x1 = 1.3, y0 = 0, y1 = 0)
arrows (x0 = 0, x1 = 0, y0 = 0, y1 = 1.3)

zdealveindy

# Euclidean vs Hellinger vs Bray-Curtis distances and double zero problem
library (vegan)
library (pals)
vltava.spe <- read.delim ('https://raw.githubusercontent.com/zdealveindy/anadat-r/master/data/vltava-spe.txt', row.names = 1)

prop_dz <- function (com)
  (nrow (com)-designdist (x = com, method = "A+B-J", terms = "binary"))/nrow (com)  # calculates proportion of double zeros

D_eucl <- dist (vltava.spe, method = 'euclidean')
D_hell <- dist (decostand (vltava.spe, method = 'hell'), method = 'euclidean')

zdealveindy

# Diversity along elevation gradient - pseudoreplication issue

# Elevation 200-1000 m asl, five elevation zones
# Richness (number of species) between 1-100 species

seed <- 56654

par (mfrow = c(2,2))

# Scenario 1: 5 replicate at each zone, each replicate at different mountain (random diversity)

zdealveindy

# Pseudoreplication issue

# 1600 quadrats sampled in 8 grids (each grid 200 quadrats)
# what happens if we consider quadrats as independent units?

DEP <- rnorm (1600)
EXP <- rnorm (1600)
GRID <- rep (1:8, each = 200)
boxplot (DEP ~ GRID)

zdealveindy

# Mia Momberg - reanalysis of JEcol dataset

# importing libraries
library (readxl)
library (tidyverse)
library (modEvA)
library (car)

# importing data from Dryad repository
url <- 'https://datadryad.org/stash/downloads/file_stream/573456'

zdealveindy

	species	WSG_obs	WSG_data	source
1	Acacia	0.539	0.9	a
2	Adansonia	0.21	0.5	b
3	Albizia	0.581	0.69	a
4	Azadirachta	0.521	0.7	a
5	Bauhinia	0.469	0.619	c
6	Bombax	0.335	0.27	d
7	Bridelia	0.557	0.62	e
8	Butea	0.377	0.465	c
9	Cassia	0.665	0.746	c