CO2                 package:datasets                 R Documentation

_C_a_r_b_o_n _D_i_o_x_i_d_e _u_p_t_a_k_e _i_n _g_r_a_s_s _p_l_a_n_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     The 'CO2' data frame has 84 rows and 5 columns of data from an
     experiment on the cold tolerance of the grass species _Echinochloa
     crus-galli_.

_U_s_a_g_e:

     CO2

_F_o_r_m_a_t:

     This data frame contains the following columns:

     _P_l_a_n_t an ordered factor with levels 'Qn1' < 'Qn2' < 'Qn3' < ... <
          'Mc1' giving a unique identifier for each plant.

     _T_y_p_e a factor with levels 'Quebec'  'Mississippi' giving the
          origin of the plant

     _T_r_e_a_t_m_e_n_t a factor with levels 'nonchilled'  'chilled'

     _c_o_n_c a numeric vector of ambient carbon dioxide concentrations
          (mL/L).

     _u_p_t_a_k_e a numeric vector of carbon dioxide uptake rates (umol/m^2
          sec).

_D_e_t_a_i_l_s:

     The CO2 uptake of six plants from Quebec and six plants from
     Mississippi was measured at several levels of ambient CO2
     concentration.  Half the plants of each type were chilled
     overnight before the experiment was conducted.

_S_o_u_r_c_e:

     Potvin, C., Lechowicz, M. J. and Tardif, S. (1990) "The
     statistical analysis of ecophysiological response curves obtained
     from experiments involving repeated measures", _Ecology_, *71*,
     1389-1400.

     Pinheiro, J. C. and Bates, D. M. (2000) _Mixed-effects Models in S
     and S-PLUS_, Springer.

_E_x_a_m_p_l_e_s:

     require(stats)
     coplot(uptake ~ conc | Plant, data = CO2, show = FALSE, type = "b")
     ## fit the data for the first plant
     fm1 <- nls(uptake ~ SSasymp(conc, Asym, lrc, c0),
        data = CO2, subset = Plant == 'Qn1')
     summary(fm1)
     ## fit each plant separately
     fmlist <- list()
     for (pp in levels(CO2$Plant)) {
       fmlist[[pp]] <- nls(uptake ~ SSasymp(conc, Asym, lrc, c0),
           data = CO2, subset = Plant == pp)
     }
     ## check the coefficients by plant
     sapply(fmlist, coef)

