population-package | R Documentation |
A package to run population simulations using an Individual-Based Model compiled in C. The population model is a discrete, age-structured model and follows the formalizing of a post-breeding Leslie matrix model.
Version 0.1 proposes functions to run and plot population projections and includes demographic and environmental stochasticities. There is also the option to parallelize simulations (except on Windows).
Version 0.2 fixes a bug that generated wrong results at very large population sizes.
Package: | population |
Type: | Package |
Version: | 0.2 |
Date: | 2018-02-05 |
License: | GPL-3 |
Guillaume Chapron <gchapron@carnivoreconservation.org>
# Initial number of individuals n0 <- 10 n1 <- 20 n2 <- 15 n3 <- 10 n4 <- 5 # Age-specific survival rates s0 <- 0.5 s1 <- 0.6 s2 <- 0.7 s3 <- 0.8 s4 <- 0.9 # Age-specific number of offspring b1 <- 0.5 b2 <- 0.8 b3 <- 1.8 b4 <- 1.8 b5 <- 1.1 # Project 10 years ahead repeated 10000 times years <- 10 runs <- 10000 results <- project( years = years, runs = runs, initial_population = c(n0, n1, n2, n3, n4), survival = cbind(c(s0, s1, s2, s3, s4), 0.0), # no environmental stochasticity litter = cbind(c(b1, b2, b3, b4, b5), 0.0) # no environmental stochasticity ) # Plot projection plot_projection(results, "mean") # Equivalent model with a post-breeding Leslie matrix postM <- matrix(nrow=5, ncol=5, byrow=TRUE, data = c( s0*b1, s1*b2, s2*b3, s3*b4, s4*b5, s0, 0, 0, 0, 0, 0, s1, 0, 0, 0, 0, 0, s2, 0, 0, 0, 0, 0, s3, 0 )) popvector <- c(n0, n1, n2, n3, n4) N <- numeric(years) N[1] <- sum(popvector) for (i in 2:years) { popvector <- postM N[i] <- sum(popvector) } # Check we get similar results lines(1:years, N, col="blue", lwd=2)
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