View source: R/best.locale_mmlt.r
best.locale | R Documentation |
A function to assess and rank possible locations for their contribution to the metapopulation
best.locale(sites, restore = FALSE, potential.sites = NULL, pop.abun, met.size=NULL, prop.philo=.85, sd.philo = 0.05, lower.upper_philo=c(lower=0, upper=1), prop.survive=0.2, sd.survive = 0.075, lower.upper_survive = c(lower=0, upper=1), dispersal, sd.dispersal, lower.upper_dispersal = c(lower=1, upper=Inf), eps = 1, mu = 2, eta = 0.5, iterations, seed=NULL)
sites |
A four-column matrix or data frame providing the name of the site (column 1) and the xy coordinates of current sites (columns 2 & 3), and area of the habitat patch (column 4) |
restore |
Logical. If TRUE, then |
potential.sites |
A three column matrix providing the name of the site (column 1) and the xy coordinates of current sites (columns 2 & 3) |
pop.abun |
A two-column data frame with mean population size in column 1 and standard deviation in column 2 |
met.size |
(Default = NULL) If specified, must be a two-column data frame with the mean (column 1) and standard deviation (column 2) of the size of metamoprhs or late-stage larvae. See Details for more information concerning this parameter. |
prop.philo |
(Default = 0.85) Mean proportion of population that are philopatric to their natal population |
sd.philo |
(Default = 0.05) Standard deviation of proportion of population that are philopatric to their natal population |
lower.upper_philo |
(Default = c(lower=0, upper=1)) Threshold lower and upper values for the proportion of philopatric individuals. Must be provided as a two-element vector with lower value first. See Details for use |
prop.survive |
(Default = 0.2) Mean survival of to adulthood. Ignored if |
sd.survive |
(Default = 0.075) Standard deviation of survival of to adulthood. |
lower.upper_survive |
(Default = c(lower=0, upper=1))Threshold lower and upper values for the proportion of individuals surviving to adulthood. Must be provided as a two-element vector with lower value first. See Details |
dispersal |
Mean dispersal distance. Should be specified in units meaningful to the coordinate system describing the spatial location of populations. See Details for how dispersal is estimated. |
sd.dispersal |
Standard deviation of dispersal distance. |
lower.upper_dispersal |
(Default = c(lower=1, upper=Inf))Threshold lower and upper values for average dispersal distance. Must be provided as a two-element vector with minimum value first. See Details |
eps |
Coefficient ([0,1]) relating to minimum patch size (Default = 1). See Details |
mu |
Number of immigrants needed for successful colonization (Default = 2). See Details |
eta |
Scaling parameter (Default = 0.5). See Details |
iterations |
Number of Monte Carlo iterations to run |
seed |
Optional to set the seed for repeatability among model runs (Default = NULL) |
If met.size
is specified, the probability of surviving to adulthood is determined using the equation:
logit(p.survive) = -1.366 + 0.87 * size
This equation comes from Altwegg & Reyer (2003). Mean and standard deviation values for met.size
must be reported in standard units such that the mean and standard deviation of observations equal zero and one, respectively (i.e. scale and center observations). In the absence of metamorph data, survival probability and variation can be specified using prop.survive
.
This model assumes uncertainty or variability in:
(1) population size;
(2) size of metamorphs OR proportion surviving;
(3) proportion of population that is philopatric;
(4) mean dispersal distance.
Uncertainty in these parameters is incorporated through repeated draws from normal distibutions with a mean and standard deviation as specified. Because some values are unrealistic (e.g., survival > 1), a truncated normal distribution is used, which requires the specification of lower and upper values. If there are no limits on the lower or upper values, then -Inf
or Inf
should be specified. Lower and upper values must be provided as a two-element vector (e.g., c(0,1)) for lower.upper_philo
, lower.upper_survive
, and lower.upper_dispersal
Probability of dispersal between two populations is determined using an incidence function wherein the probability of connectivity is a negative exponential relationship with 1/mean dispersal controlling the rate of decay.
This function returns a list with two components: (1) $summary.df
is a data frame with the results averaged over all Monte Carlo iterations, and (2) $results.list
is a list of length equal to the number of Monte Carlo iterations and contains the raw results from the analysis.
Elements of the summary data frame include:
(1) mmlt
: The log10 of the Metapopulation Mean Lifetime;
(2) rank
: The rank order importance based on mmlt;
(3) frq_col
: The frequency that 2 or more individuals immigrated into a population. This metric is used to adjust mmlt for likelihood of colonization;
(4) mmlt_col
: The product of mmlt and frq_col;
(5) rank_adj
: The rank importance of each potential location based on the product of mmlt and the frequency of colonization (frq_col)
Bill Peterman <Peterman.73@osu.edu>
Altwegg, R., and H.-U. Reyer. 2003. Patterns of natural selection on size at metamorphosis in water frogs. Evolution 57:872-882.
ssmc_summary
## Assess potential new locations best_results <- best.locale(sites = site.dat[,1:4], potential.sites = potential.dat, pop.abun = site.dat[,5:6], met.size = site.dat[,7:8], prop.philo = 0.95, sd.philo = 0.05, lower.upper_philo=c(lower=0, upper=1), # prop.survive=0.2, ## Not needed b/c met.size is specified # sd.survive = 0.075, ## Not needed b/c met.size is specified lower.upper_survive = c(lower=0, upper=1), dispersal = 25, sd.dispersal = 10, lower.upper_dispersal = c(lower=10, upper=Inf), eps = 1, mu = 2, eta = 0.5, iterations = 10, seed = 123) ## Assess existing locations for restoration best_results <- best.locale(sites = site.dat[,1:4], restore = TRUE, pop.abun = site.dat[,5:6], met.size = site.dat[,7:8], prop.philo = 0.95, sd.philo = 0.05, lower.upper_philo=c(lower=0, upper=1), # prop.survive=0.2, ## Not needed b/c met.size is specified # sd.survive = 0.075, ## Not needed b/c met.size is specified lower.upper_survive = c(lower=0, upper=1), dispersal = 25, sd.dispersal = 10, lower.upper_dispersal = c(lower=10, upper=Inf), eps = 1, mu = 2, eta = 0.5, iterations = 10, seed = 123)
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