ACE | R Documentation |
Calculate the number of unobserved species (f0).
ACE(f)
Chao1(f)
Clench(f, pct.n = 0.85, num.reps = 100)
Swor1(f, N)
iChao1(f)
jack1(f)
jack2(f)
f |
a vector of species frequencies where |
pct.n |
percent of samples to use in bootstrap draws. Must be in range of |
num.reps |
number of random re-orderings of samples to fit curve to. |
N |
population size. |
All functions return a vector containing the estimated number of
species (s.est
), unobserved species (f0
), observed species
(s.obs
), and the total number of samples (n
). Swor1
also returns the standard deviation of s.est
as sd.s.est
.
Eric Archer eric.archer@noaa.gov
Chao1, ACE
Colwell, R.K., A. Chao, N.J. Gotelli, S.-Y. Lin, C.X. Mao, R.L. Chazdon, and J.T. Longino. 2012. Models and estimators linking individual-based and sample-based rarefaction, extrapolation and comparison of assemblages. Journal of Plant Ecology 5(1):3-21.
jack1, jack2
Burnham, KP and WS Overton. 1978. Estimation of the size of a closed population when capture probabilities vary among animals. Biometrika 65(3):625-633.
Swor1
Chao, A. and C.-W. Lin. 2012. Nonparametric lower bounds for species richness and shared species richness under sampling without replacement. Biometrics 68:912-921.
iChao1
Chiu, C-H, Wang, Y-T, Walther, BA, and A Chao. 2014. An impro.ved nonparametric lower bound of species richness via a modified Good-Turing frequency formula. Biometrics 70(3):671-682.
clench
Clench, H. 1979. How to make regional lists of butterflies: Some thoughts. Journal of the Lepidopterists' Society 33(4):216-231.
data(osa.second.growth)
f <- expand.freqs(osa.second.growth)
ace.est <- ACE(f)
chao1.est <- Chao1(f)
jack1.est <- jack1(f)
jack2.est <- jack2(f)
swor1.est <- Swor1(f, 20000)
ichao1.est <- iChao1(f)
clench.est <- Clench(f, num.reps = 50)
f0.est <- cbind(
ACE = ace.est["f0"],
Chao1 = chao1.est["f0"],
jack1 = jack1.est["f0"],
jack2 = jack2.est["f0"],
Swor1 = swor1.est["f0"],
iChao1 = ichao1.est["f0"],
clench = clench.est["f0"]
)
f0.est
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