specpool                package:vegan                R Documentation

_E_x_t_r_a_p_o_l_a_t_e_d _S_p_e_c_i_e_s _R_i_c_h_n_e_s_s _i_n _a _S_p_e_c_i_e_s _P_o_o_l

_D_e_s_c_r_i_p_t_i_o_n:

     The function estimates the extrapolated species richness in a
     species pool, or the number of unobserved species.

_U_s_a_g_e:

     specpool(x, pool)
     specpool2vect(X, index = c("Jack.1","Jack.2", "Chao", "Boot", "Species"))

_A_r_g_u_m_e_n_t_s:

       x: Data frame or matrix with species data.

    pool: A vector giving a classification for pooling the sites in the
          species data. If missing, all sites are pooled together.

       X: A 'specpool' result object.

   index: The selected index of extrapolated richness.

_D_e_t_a_i_l_s:

     Many species will always remain unseen or undetected in a
     collection of sample plots.  The function uses some popular ways
     of estimating the number of these unseen species and adding them
     to the observed species richness (Palmer 1990, Colwell &
     Coddington 1994).

     In the following, S_P is the extrapolated richness in a pool, S_0
     is the observed number of species in the collection, a1 and a2 are
     the number of species occurring only in one or only in two sites
     in the collection, p_i is the frequency of species i, and N is the
     number of sites in the collection.  The variants of extrapolated
     richness are:

       Chao                    S_P = S_0 + a1/2/a2
       First order jackknife   S_P = S_0 + a1*(N-1)/N
       Second order jackknife  S_P = S_0 + a1*(2*n-3)/n - a2*(n-2)^2/n/(n-1)
       Bootstrap               S_P = S_0 + Sum (1-p_i)^N

_V_a_l_u_e:

     The function returns a data frame with entries for observed
     richness and each of the indices for each class in 'pool' vector. 
     The utility function 'specpool2vect' maps the pooled values into a
     vector giving the value of selected 'index' for each original
     site.

_N_o_t_e:

     The functions are based on assumption that there is a species
     pool: The community is closed so that there is a fixed pool size
     S_P. Such cases may exist, although I have not seen them yet.  All
     indices are biased for open communities.

     An approximate ("traditional") variant is used for the Chao index.

     The function is still preliminary.  I may add variances, although
     these seem to be biased and confusing.

     See <URL: http://viceroy.eeb.uconn.edu/EstimateS> for a more
     complete (and positive) discussion and alternative software for
     some platforms.

_A_u_t_h_o_r(_s):

     Jari Oksanen

_R_e_f_e_r_e_n_c_e_s:

     Colwell, R.K. & Coddington, J.A. (1994). Estimating terrestrial
     biodiversity through extrapolation. _Phil. Trans. Roy. Soc.
     London_ B 345, 101-118.

     Palmer, M.W. (1990). The estimation of species richness by
     extrapolation. _Ecology_ 71, 1195-1198.

_S_e_e _A_l_s_o:

     'veiledspec', 'diversity'.

_E_x_a_m_p_l_e_s:

     data(dune)
     data(dune.env)
     attach(dune.env)
     pool <- specpool(dune, Management)
     pool
     op <- par(mfrow=c(1,2))
     boxplot(specnumber(dune) ~ Management, col="hotpink", border="cyan3",
      notch=TRUE)
     boxplot(specnumber(dune)/specpool2vect(pool) ~ Management, col="hotpink",
      border="cyan3", notch=TRUE)
     par(op)

