SPecies Association Analysis

Description

Miscellaneous functions for analysis of species association and niche overlap.

Details

Author(s)

Author: Jinlong Zhang jinlongzhang01@gmail.com

Maintainer: Jinlong Zhang jinlongzhang01@gmail.com

Examples

data(testdata)
testdata

data(splist)
splist

### data tranformation
(spmatrix <- data2mat(testdata))
#Species association
sp.assoc(spmatrix)

# Species association between each pair of species
(result <- sp.pair(spmatrix))

#### Niche width and niche overlap
data(datasample)
niche.overlap.boot(datasample[,1:3], method = "levins")
niche.overlap(datasample, method = "levins")
niche.width(datasample[,1:3], method = "shannon")

##example turnover()
plotlab1 <- XYname(4,6)
xxx <- 1:240
dim(xxx) <- c(24, 10)
rownames(xxx) <- plotlab1

### Distance between each pair of plots
ddd <- dist(xxx)

### label matrix
labmat1 <- lab.mat(plotlab1)
yyy <- turnover(labmat1, ddd)

## geodist() example
## Paris
L1 = deg2dec(-2,20,14)
phi1 = deg2dec(48, 50, 11)
## Washington DC
L2 = deg2dec(77,03,56)
phi2 = deg2dec(38,55,17)

##High precision Great Circle distance
geodist(L1, phi1, L2, phi2)

Generating vector of XY labels

Description

Generating vector of XY labels by providing number of rows and columns

Usage

XYname(x, y)

Arguments

Value

Vector of XY labels

Author(s)

Jinlong Zhang jinlongzhang01@gmail.com

References

None

See Also

lab.mat for converting the vector to matrix of XY labels.

Examples

## XYname() example
XYname(4,6)

Convert field records to community matrix

Description

Convert field records to community matrix

Usage

data2mat(data = data)

Arguments

Value

Return a community matrix ready for computing diversity indices.

Author(s)

Jinlong Zhang jinlongzhang01@gmail.com

References

None

Examples

data(testdata)
spmatrix <- data2mat(testdata)

A sample dataset for a community

Description

A sample community matrix containing 8 plots and 14 species, from Gutianshan, Zhejiang, China.

Usage

data(datasample)

Details

Values are the importance value for each species.

Source

Hu Zheng-hua, Qian Hai-Yuan, Yu Ming-jian. 2009. The niche of dominant species populations in Castanopsis eyrei forest in Gutian Mountain National Natural Reserve. Acta Ecologica Sinica. Vol.29, 3670-3677

Examples

data(datasample)
datasample

Degree to decimal

Description

Convert latitude or longitude from degree to decimal format

Usage

deg2dec(h, m, s)

Arguments

Details

Convert latitude or longitude from degree to decimal format.

Value

Degree of decimal format

Note

Places with eastern hemisphere should have longitude and southern hemisphere less than zero.

Author(s)

Jinlong Zhang jinlongzhang01@gmail.com

Examples

## deg2dec() example
##Paris
L1 = deg2dec(-2,20,14)
phi1 = deg2dec(48, 50, 11)
##Washington DC
L2 = deg2dec(77,03,56)
phi2 = deg2dec(38,55,17)

Convert distance matrix to pairwised list

Description

Convert distance matrix to pairwised list

Usage

dist2list(dist)

Arguments

Details

Pairwise list with first column indicates the rows of the original distance matrix, second column indicates the columns indicates the rows of the original distance matrix, and the third indicats the values.

Value

Dataframe with three columns.

Author(s)

Jinlong Zhang jinlongzhang01@gmail.com

References

Tuomisto, H. (2003). "Dispersal, Environment, and Floristic Variation of Western Amazonian Forests." Science 299(5604): 241-244.

See Also

list2dist

Examples

##dist2list() example
x <- matrix(rnorm(100), nrow=5)
sampledata <- dist(x)
ddd <- dist2list(sampledata)

Compute species' relative frequency

Description

Computing species' relative frequency as defined by the numbers of plots having a species divided by the total number of plots.

Usage

freq.calc(matr)

Arguments

Details

The input should be a standard community matrix with rows representing sites and columns representing species.

Value

A vector containing relative frequency for each species

Author(s)

Jinlong Zhang jinlongzhang01@gmail.com

References

None

Examples

data(testdata)
spmatrix <- data2mat(testdata)
freq.calc(spmatrix)

Hight precision Great circle distance between two places

Description

Hight precision Great circle distance between two places assuming the earth is elliptic sphere.

Usage

geodist(L1, phi1, L2, phi2)

Arguments

Details

Hight precision great circle distance between two places assuming the earth is elliptic sphere.

Value

Hight precision great circle distance.

Author(s)

Jinlong Zhang jinlongzhang01@gmail.com

References

Jean Meeus 1991 Astronomical Algorithms Willmann-Bell 80-83

See Also

lgeodist

Examples

## geodist() example
## Paris
L1 = deg2dec(-2,20,14)
phi1 = deg2dec(48, 50, 11)
## Washington DC
L2 = deg2dec(77,03,56)
phi2 = deg2dec(38,55,17)
##High precision Great Circle distance
geodist(L1, phi1, L2, phi2)

Convert vector of XY labels to label matrix

Description

Convert vector of XY labels to label matrix

Usage

lab.mat(plotlab)

Arguments

Value

XY label matrix

Author(s)

Jinlong Zhang jinlongzhang01@gmail.com

See Also

turnover

Examples

### lab.mat() example
plotlab1 <- XYname(4,6)
labmat <- lab.mat(plotlab1)

Low precision Great circle distance between two places

Description

Calculating Great circle distance between two places assuming that the earth is sphere.

Usage

lgeodist(L1, phi1, L2, phi2)

Arguments

Value

Low precision great circle distance between two places.

Note

This function assuming that the earth is sphere.

Author(s)

Jinlong Zhang jinlongzhang01@gmail.com

References

Jean Meeus 1991 Astronomical Algorithms Willmann-Bell 80-81

See Also

geodist

Examples

#lgeodist() example
##Paris
L1 = deg2dec(-2,20,14)
phi1 = deg2dec(48, 50, 11)
##Washington DC
L2 = deg2dec(77,03,56)
phi2 = deg2dec(38,55,17)
#Great circle distance
lgeodist(L1, phi1, L2, phi2)

Convert pairwise list to distance matrix

Description

Convert pairwise list to distance matrix

Usage

list2dist(dat)

Arguments

Details

Dataframe with first column as the column names in the distance matrix, second column as the rownames in the distance matrix, third column the values.

Value

distance matrix

Author(s)

Jinlong Zhang jinlongzhang01@gmail.com

References

Tuomisto, H. (2003). "Dispersal, Environment, and Floristic Variation of Western Amazonian Forests." Science 299(5604): 241-244.

See Also

dist2list

Examples

##list2dist() example
x <- matrix(rnorm(100), nrow=5)
sampledata <- dist(x)
ddd <- dist2list(sampledata)
list2dist(ddd)

Niche overlap between each pair of species

Description

Compute niche overlap between each pair of species.

Usage

niche.overlap(mat, method = c("levins", "schoener",
       "petraitis", "pianka", "czech", "morisita"))

Arguments

Details

To add.

Value

A distance matrix contains niche overlap index between each pair of species.

Author(s)

Jinlong Zhang jinlongzhang01@gmail.com

References

Zhang Jin-tun,(2004 ) Quantitative Ecology, Science Press, Beijing

Nicholas J. Gotelli. 2000. Null model analysis of species co-occurrence patterns. Ecology 81:2606-2621. http://esapubs.org/archive/ecol/E081/022/EcoSim

See Also

niche.overlap.pair

Examples

data(datasample)
niche.overlap(datasample, method = "levins")

Boostrap niche overlap indices

Description

Bootstrap niche overlap indices

Usage

niche.overlap.boot(mat, method = c("pianka", "schoener", "petraitis",
    "czech", "morisita", "levins"), times = 1000, quant = c(0.025, 0.975))

Arguments

Details

This function bootstraps the following niche overlap indices between each pair of species: \ schoener: Schoener's niche overlap index\ petraitis: Petraitis' niche overlap index\ czech: Czechanowski index \ morisita: Morisita's overlap index\ levins: Levin's overlap index\ see more information from Gotelli, N(2009).\

Value

a data frame with each row for each pair of species the columns are "Observed", "Boot mean", "Boot std", "Boot CI1", "Boot CI2", "times"

Author(s)

Jinlong Zhang jinlongzhang01@gmail.com

References

Zhang Jin-tun,(2004 ) Quantitative Ecology, Science Press, Beijing\

Nicholas J. Gotelli. 2000. Null model analysis of species co-occurrence patterns. Ecology 81:2606-2621. http://esapubs.org/archive/ecol/E081/022/EcoSim

See Also

niche.overlap.boot.pair

Examples

data(datasample)
niche.overlap.boot(datasample[,1:4], method = "pianka")
niche.overlap.boot(datasample[,1:4], method = "schoener")
niche.overlap.boot(datasample[,1:4], method = "czech")
niche.overlap.boot(datasample[,1:4], method = "levins")

Boostrap the niche overlap indices

Description

bootstrap the niche overlap indices between a pair of species. This is an internal function used by niche.overlap.boot, use niche.overlap.boot instead.

Usage

niche.overlap.boot.pair(vectorA, vectorB, method = c("levins",
     "schoener", "petraitis", "pianka", "czech", "morisita"),
      times = 1000, quant = c(0.025, 0.975))

Arguments

Value

This function will return a vector containing:\ "Observed", \ "Boot mean", \ "Boot std", \ "Boot CI1", \ "Boot CI2", \ "times" \

Note

This is an internal function, please use niche.overlap.boot.

Author(s)

Jinlong Zhang jinlongzhang01@gmail.com

References

Zhang Jin-tun,(2004 ) Quantitative Ecology, Science Press, Beijing

See Also

niche.overlap.boot

Examples

data(datasample)
niche.overlap.boot.pair(datasample[,1], datasample[,2], method = "levins")

Compute niche overlap index between two species

Description

Compute niche overlap index between two species. This is an internal function, used niche.overlap instead.

Usage

niche.overlap.pair(vectA, vectB, method = c("pianka",
     "schoener","petraitis","czech","morisita", "levins"))

Arguments

Details

None

Value

The niche overlap index

Author(s)

Jinlong Zhang jinlongzhang01@gmail.com

References

Zhang Jin-tun,(2004 ) Quantitative Ecology, Science Press, Beijing

Nicholas J. Gotelli. 2000. Null model analysis of species co-occurrence patterns. Ecology 81:2606-2621. http://esapubs.org/archive/ecol/E081/022/EcoSim

See Also

niche.overlap

Examples

data(datasample)
niche.overlap.pair(datasample[,1],datasample[,2], method = "levins")

Niche width

Description

Compute niche width for all the species in a community.

Usage

niche.width(mat, method = c("shannon", "levins"))

Arguments

Value

A vetor containing niche width for all the species in the community.

Author(s)

Jinlong Zhang jinlongzhang01@gmail.com

References

Zhang Jin-tun,(2004 ) Quantitative Ecology, Science Press, Beijing

See Also

niche.overlap for niche overlap

Examples

data(datasample)
niche.width(datasample, method = "levins")
niche.width(datasample, method = "shannon")

Analyzing species association

Description

Analyzing species association

Usage

sp.assoc(matr)

Arguments

Details

Computations are based on the following formula.

If, N: Number of plots.

S: Number of species.

n: Number of plots occupied by certain species.

Tj: total number of species for each plot. s t: mean species number for all the plots.

Then: Variance of species relative frequency is: sigma^{2}{T}= sum{i}=1^{s}P{i}(1-P{i}).

Variance of species number is: S^{2}{T}=({1}{N})sum{j=1}^{N}(T{j}-t)^{2} .

Species relative frequency: P{i}={n{i}}{N}.

Variance ratio:

If VR > 1 Positively associated,

If VR < 1 Negative associated

VR = {S{T}^{2}}/{sigma{T}^{2}}

W: used in comparison with chi square with n degrees of freedom.

W = VR * N

Value

Variance ratio, W, Chisq, etc, see details

Author(s)

Jinlong Zhang jinlongzhang01@gmail.com

References

Zhang Qiaoying, Peng Shaolin, Zhang Sumei, Zhang Yunchun, Hou Yuping. (2008) Association of dormintant species in Guia hill Municipal Park of Macao. Ecology and Environment. 17:1541-1547

GUO zhongling, MA yuandan, ZHENG Jiping, LIU Wande , JIN Zefeng.(2004) Biodiversity of tree species,their populations'spatial distribution pattern and interspecific association in mixed deciduous broadleaved forest in Changbai Mountains. Chinese Journal of Applied Ecology. 15:2013-2018

Shi Zuomin, Liu Shirong, Cheng Ruimei, Jiang Youxu.(2001) Interspecific association of plant populations in deciduous broad leaved forest in Baotianman. Scientia Silvae Sinicae. 37:30-35

See Also

See also sp.pair for association between each pair of species.

Examples

data(testdata)
spmatrix <- data2mat(testdata)
sp.assoc(spmatrix)

Species association between each pair of species

Description

Compute species association between each pair of species.

Usage

sp.pair(matr)

Arguments

Details

If a, b, c, d denote the co-occurrence the two species A and B, where:

a = number of plots occupied both by A and B.

b = number of plots only have A.

c = number of plots only have B.

d = number of plots without A or B.

N = a+b+c+d

Then, it is possible to compute:

Chi square (Yate's correction): chi^{2}=((((a*d-b*c)-0.5*N)^2)*N)/(a+b)*(a+c)*(b+d)*(c+d)

V ratio: V = ((a+d)-(b+c))/(a + b + c + d)

Jaccard index: Jaccard =a/(a + b + c)

Ochiai index: Ochiai = a/sqrt((a+b)*(a+c))

Dice index: Dice = 2*a/(2*a + b + c)

The Association Coefficient(AC):

if a*d >= b*c:

AC = (a*d - b*c)/((a+b)*(b+d))

if a*d < b*c and a <= d:

AC = (a*d - b*c)/((a+b)*(a+c))

if a*d < b*c and a > d:

AC = (a*d - b*c)/((b+d)*(c+d))

Point correlation coefficient

(PCC):

PCC = {a*d-b*c}/{(a+b)*(a+c)*(c+d)*(b+d)}

Value

Author(s)

Jinlong Zhang jinlongzhang01@gmail.com

References

HURLBERT, S. H. (1969). A coefficient of interspecific association. Ecology, 50(1), 1-9.

WANG, B. S., & PENG S. L. (1985). Studies on the Measuring Techniques of Interspecific Association of Lower-Subtropical Evergreen-Broadleaved Forests. I. The Exploration and the Revision on the Measuring Formulas of Interspecific Association. Chinese Journal of Plant Ecology, 9(4), 274-285.

JIAN, M. F., LIU, Q. J., ZHU, D., & YOU, H. (2009). Inter-specific correlations among dominant populations of tree layer species in evergreen broad-leaved forest in Jiulianshan Mountain of subtropical China. Chinese Journal of Plant Ecology, 33(4), 672-680.

ZHOU, X. Y., WANG, B. S., LI, M. G., & ZAN, Q. J. (2000). An analysis of interspecific associations in secondary succession forest communities in Heishiding Natural Reserve, Guangdong Province. Chinese Journal of Plant Ecology, 24(3), 332-339

See Also

See Also as sp.assoc for computing association for all the species.

Examples

data(testdata)
spmatrix <- data2mat(testdata)
result <- sp.pair(spmatrix)

A sample dataframe showing species taxonomic information (Deprecated)

Description

A sample dataframe containing the checklist of species used in add.col()

Usage

data(splist)

Format

A data frame with 9 observations on the following 3 variables.

species

a factor with levels sp1 to sp8

genera

a factor with levels gen1 to gen6

family

a factor with levels fam1 to fam5

References

None

Examples

data(splist)
data(testdata)

Subset species based on relative frequency

Description

Subset species based on relative frequency.

Usage

sub.sp.matrix(spmatrix, freq = 0.5, common = NULL)

Arguments

Details

sub.sp.matrix will select the species whose relative frequency above 0.5 (default), or select certain number of species based on relative frequency.

Value

A subset matrix of species with high relative frequency.

Author(s)

Jinlong Zhang jinlongzhang01@gmail.com

References

None

See Also

See Also subset

Examples

library(vegan)
data(BCI)
## Select the species whose relative frequency
## more than 0.5, from BCI data
sub <- sub.sp.matrix(BCI, freq = 0.5)
## Select the top 30 species according to relative frequency
sub <- sub.sp.matrix(BCI, common = 30)

A sample dataset s

Description

A sample dataset

Usage

data(testdata)

Format

A dataframe with 11 observations on the following 3 variables.

plotname

a factor with levels plot1, plot2, plot3.

species

a factor with levels sp1 to sp7.

abundance

a numeric vector indicating number of individuals appeared in each plot.

Examples

data(testdata)
testdata

Calculating species turnover

Description

Calculating species turnover based on the mean value between focus quadrat and their neighbours.

Usage

turnover(lab.mat, dist.mat, type = c("quart", "octal"))

Arguments

Details

species turnover based on the mean value between centred quadrat and its neighbours.

Value

matrix with species turnover.

Author(s)

Jinlong Zhang jinlongzhang01@gmail.com

References

Lennon J. 2001 The geographical structure of British bird distributions - diversity, spatial turnover and scale Journal of Animal Ecology 70,966-979

See Also

XYname and lab.mat

Examples

##example turnover()
plotlab1 <- XYname(4,6)
xxx <- 1:240
dim(xxx) <- c(24, 10)
rownames(xxx) <- plotlab1
### Distance between each pair of plots
ddd <- dist(xxx)
### label matrix
labmat1 <- lab.mat(plotlab1)
yyy <- turnover(labmat1, ddd)