This function estimates growth parameters from tagging data. Munro plot is applied
a list consisting of following parameters:
indicating which of following methods should be applied: "GullandHolt" or "Munro".
two values indicating the lower and upper limits of the range, in which the optimise searches for the Linf value with the best fit (lowest CV value ),
indicating the unit of the time interval, either "year", "month", "week", or "day"
If Munro plot is applied the optimal Linf value is found by minimizing the coefficient of variation (CV = sd(K)/mean(K)). For this iterative method the optimise function is applied. The histogram of the individual K values allows to distinguish potential differences in growth performance between individuals. t0 can not be estimated by Munro plot, neither by the Gulland Holt method.
A list with the input parameters and following parameters:
x: independent variable used for regression analysis,
y: dependent variable used for regression analysis,
reg_coeffs: regression coefficients,
r2: r squared of regression analysis,
Linf: infinite length for investigated species in cm [cm],
K: growth coefficent for investigated species per year [1/year],
conf_int_K: confidence intervals of K (only if Gulland Holt method was applied).
Sparre, P., Venema, S.C., 1998. Introduction to tropical fish stock assessment. Part 1. Manual. FAO Fisheries Technical Paper, (306.1, Rev. 2). 407 p.
Sparre, P., Venema, S.C., 1999. Introduction to tropical fish stock assessment. Part 2. Excercises. FAO Fisheries Technical Paper, (306.2, Rev. 2). 94 p.
Wolff, M., 1984. Early setback for scallop culture in Peru.
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# from Wolff (1984) dat <- list(L1 = c(40,46,29,30,18,31,48,49,59,58,61,65,57,55), L2 = c(85,53,55,56,25,43,70,59,62,80,72,83,65,56), delta_t = c(289,26,84,77,14,38,89,38,28,149,89,74,38,21)) growth_tagging(param = dat, "Munro", time_unit = "day", Linf_range=c(80,120)) growth_tagging(param = dat, "GullandHolt", time_unit = "day") # from Sparre and Venema (1999) dat <- list(L1 = c(9.7,10.5,10.9,11.1,12.4,12.8,14.0,16.1,16.3,17.0,17.7), L2 = c(10.2,10.9,11.8,12.0,15.5,13.6,14.3,16.4,16.5,17.2,18.0), delta_t = c(53,33,108,102,272,48,53,73,63,106,111)) growth_tagging(param = dat, "Munro", time_unit = "day", Linf_range = c(10,40)) growth_tagging(param = dat, "GullandHolt", time_unit = "day")
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