oribatid                package:ade4                R Documentation

_O_r_i_b_a_t_i_d _m_i_t_e

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

     This data set contains informations about environmental control
     and spatial structure in ecological communities of Oribatid mites.

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

     data(oribatid)

_F_o_r_m_a_t:

     'oribatid' is a list containing the following objects : 

     _f_a_u : a data frame with 70 rows (sites) and 35 columns (Oribatid
          species)   

     _e_n_v_i_r : a data frame with 70 rows (sites) and 5 columns
          (environmental variables)

     _x_y : a data frame that contains spatial coordinates of the 70
          sites

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

     Variables of 'oribatid$envir' are the following ones : 
      substrate: a factor with seven levels that describes the nature
     of the substratum
      shrubs: a factor with three levels that describes the
     absence/presence of shrubs
      topo: a factor with two levels that describes the microtopography
      density: substratum density (g.L^-1)
      water: water content of the substratum (g.L^-1)

_S_o_u_r_c_e:

     Data prepared by P. Legendre Pierre.Legendre@umontreal.ca and 
      D. Borcard borcardd@magellan.umontreal.ca starting from 
      <URL:
     http://www.fas.umontreal.ca/biol/casgrain/fr/labo/oribates.html>

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

     Borcard, D., and Legendre, P. (1994) Environmental control and
     spatial structure in ecological communities: an example using
     Oribatid mites (_Acari Oribatei_). _Environmental and Ecological
     Statistics_, *1*, 37-61.

     Borcard, D., Legendre, P., and Drapeau, P. (1992) Partialling out
     the spatial component of ecological variation. _Ecology_, *73*,
     1045-1055.

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

     data(oribatid)
     ori.xy <- oribatid$xy[,c(2,1)]
     names(ori.xy) <- c("x","y")
     plot(ori.xy,pch = 20, cex = 2, asp = 1)

     if (require(tripack, quiet = TRUE)) {
       if (require(spdep, quiet = TRUE)) {
         plot(voronoi.mosaic(ori.xy), add = TRUE)
         s.label(ori.xy, add.p = TRUE,
          neig = nb2neig(knn2nb(knearneigh(as.matrix(ori.xy), 3))),
          clab = 0)
         }
       }

