abund                package:pastecs                R Documentation

_S_o_r_t _v_a_r_i_a_b_l_e_s _b_y _a_b_u_n_d_a_n_c_e

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

     Sort variables (usually species in a species x stations matrix) in
     function of their abundance, either in number of non-null values,
     or in number of individuals (in log). The 'f' coefficient allows
     adjusting weight given to each of these two criteria.

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

     abund(x, f=0.2)
     ## S3 method for class 'abund':
     summary(abd)
     ## S3 method for class 'abund':
     plot(abd, n=abd$n, lvert=TRUE, lvars=TRUE, lcol=2, llty=2,
             all=TRUE, dlab=c("cumsum", "% log(ind.)", "% non-zero"),
             dcol=c(1, 2, 4), dlty, dpos=c(1.5, 20), ...)
     ## S3 method for class 'abund':
     lines(abd, n=abd$n, lvert=TRUE, lvars=TRUE, ...)
     ## S3 method for class 'abund':
     identify(abd, label.pts=FALSE, lvert=TRUE, lvars=TRUE, ...)
     ## S3 method for class 'abund':
     extract(abd, n=abd$n, left=TRUE)

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

       x: A data frame containing the variables to sort according to
          their abundance in columns 

       f: Weight given to the number of individuals criterium (strictly
          included between 0 and 1; weight for the non-null values is
          '1-f'. The default value, 'f=0.2', gives enough weight to the
          number of non-null values to get abundant species according
          to this criterium first, but allowing to get at the other
          extreme rare, but locally abundant species 

     abd: An 'abund' object returned by 'abund' 

       n: The number of variables selected at left 

   lvert: If 'TRUE' then a vertical line separate the n variables at
          left from the others 

   lvars: If 'TRUE' then the x-axis labels of the n left variables are
          printed in a different color to emphasize them 

    lcol: The color to use to draw the vertical line ('lvert=TRUE') and
          the variables labels ('lvars=TRUE') at left af the nth
          variable. By default, color 2 is used 

    llty: The style used to draw the vertical line ('lvert=TRUE'). By
          default, a dashed line is used 

     all: If 'TRUE' then all lines are drawn (cumsum, %log(ind.) and
          %non-null). If 'FALSE', only the cumsum line is drawn 

    dlab: The legend labels 

    dcol: Colors to use for drawing the various curves on the graph 

    dlty: The line style to use for drawing the various curves on the
          graph 

    dpos: The position of the legend box on the graph (coordinates of
          its top-left corner). A legend box is drawn only if
          'all=TRUE' 

     ...: additional graph parameters 

label.pts: Do we have to label points on the graph or to chose an
          extraction level with the 'identify()' method? 

    left: If 'TRUE', the n variables at left are extracted. Otherwise,
          the total-n variables at right are extracted 

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

     Successive sorts can be applied. For instance, a first sort with
     'f = 0.2', followed by an extraction of rare species and another
     sort with 'f = 1' allows to collect only rare but locally abundant
     species.

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

     An object of type 'abund' is returned. It has methods 'print()',
     'summary()', 'plot()', 'lines()', 'identify()', 'extract()'.

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

     Philippe Grosjean (phgrosjean@sciviews.org), Frdric Ibanez
     (ibanez@obs-vlfr.fr)

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

     Ibanez, F., J.-C. Dauvin & M. Etienne, 1993. _Comparaison des
     volutions  long terme (1977-1990) de deux peuplements
     macrobenthiques de la baie de Morlaix (Manche occidentale):
     relations avec les facteurs hydroclimatiques._ J. Exp. Mar. Biol.
     Ecol., 169:181-214.

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

     'escouf'

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

     data(bnr)
     bnr.abd <- abund(bnr)
     summary(bnr.abd)
     plot(bnr.abd, dpos=c(105, 100))
     bnr.abd$n <- 26
     # To identify a point on the graph, use: bnr.abd$n <- identify(bnr.abd)
     lines(bnr.abd)
     bnr2 <- extract(bnr.abd)
     names(bnr2)

