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); require(graphics) coplot(uptake ~ conc | Plant, data = CO2, show.given = 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)