Zoogrowth          package:marelacTeaching          R Documentation

_a _z_o_o_p_l_a_n_k_t_o_n _g_r_o_w_t_h _d_a_t_a_s_e_t

_D_e_s_c_r_i_p_t_i_o_n:

     This literature dataset, compiled by Hansen et al. (1997) contains
     84 measurements of maximal growth rates as a function of organism
     volume and temperature for various species of zooplankton. The
     maximal growth rates were obtained from laboratory experiments.

     It is used in the book to demonstrate how one can obtain
     order-of-magnitude estimates of model parameters (i.c. maximal
     growth) via allometric relations, i.e. by performing log-log
     regression of organism rates versus size.

_U_s_a_g_e:

     Zoogrowth

_F_o_r_m_a_t:

     a dataframe with 84 rows, and with following columns:

     _V_o_l_u_m_e the volume in [um 3].

     _M_u_m_a_x the maximal growht rate, [/hour].

     _S_p_e_c_i_e_s the name of reared zooplankton species.

     _T_e_m_p the rearing temperature, [dg C].

     _G_r_o_u_p the systematic group to which the organism belongs, one of
          Nanoflagellate, Dinoflagellate, Ciliate, Rotifer,
          Meroplankton, Copepod.

_A_u_t_h_o_r(_s):

     Karline Soetaert <k.soetaert@nioo.knaw.nl>

_R_e_f_e_r_e_n_c_e_s:

     Hansen PJ, Bjornsen PK, Hansen BW, 1997. Zooplankton grazing and
     growth: Scaling within the 2-2,000-mu m body size range. Limnology
     and Oceanograpy 42: 687-704.

_S_e_e _A_l_s_o:

     'SCOC', a dataset containing sediment community oxygen consumption
     rates

     See the paper of Hansen et al. 1997 for a description of the
     original literature sources of this dataset.

_E_x_a_m_p_l_e_s:

     plot(Zoogrowth$Volume,Zoogrowth$Mumax,log="xy",
           xlab="zooplankton volume, micrometer ^ 3",
           ylab="maximal growth rate, /hr",main="Zoogrowth",cex=2,
           pch=(15:20)[Zoogrowth$Group],col=(1:6)[Zoogrowth$Group])
     legend("topright",legend=levels(Zoogrowth$Group),col=1:6,pch=15:20)

     ll <- lm(log(Zoogrowth[,2])~ log(Zoogrowth[,1]))
     rr <- summary(ll)$r.squared
     A  <- exp(coef(ll)[1])
     B  <- (coef(ll)[2])
     curve(A*x^B,add=TRUE,lwd=2)
     AA <- round(A*100)/100
     BB <- round(B*100)/100
     expr <- substitute(y==A*x^B,list(A=AA,B=BB))
     text(100,.0035,expr,adj=0)
     expr2 <- substitute(r^2==rr,list(rr=round(rr*100)/100))
     text(100,0.002,expr2, adj=0)

