relative_probabilities_of_vicariants: Calculate probability of different descendant rangesizes, for...
In BioGeoBEARS: BioGeography with Bayesian (and Likelihood) Evolutionary Analysis in R Scripts

Description Usage Arguments Details Value Note Author(s) References See Also Examples

"Rangesize" here means "number of areas in a geographic range". The LAGRANGE cladogenesis model requires that, during cladogenesis events, one daughter lineage will ALWAYS have a geographic range of size 1. This is argued for in Ree et al. (2008) on the grounds that new species usually get isolated and start in a new area. This is a reasonable proposition, but still, it would be nice to test the assumption. In addition, it could be that some speciation modes, especially vicariance, obey different rules. E.g., DIVA (Ronquist (1996), Ronquist (1997)) allows vicariant speciation to divide up the ancestral range in every possible way (e.g., ABCD–>AB|CD, or AC|BD, or A|BCD, or D|ABC, etc.), but LAGRANGE would only allow vicariance to split off areas of size 1: (ABCD–>A|BCD, B|ACD, etc.) (Ronquist_Sanmartin_2011).

1 2	relative_probabilities_of_vicariants(max_numareas = 6, maxent_constraint_01v = 1e-04, NA_val = NA)

`max_numareas`	The maximum number of areas possible allowed for the smaller-ranged-daughter in this type of cladogenesis/speciation.
`maxent_constraint_01v`	The parameter describing the probability distribution on descendant rangesizes for the smaller descendant, in a vicariance event (where the maximum size of the smaller range is numareas/2, rounded down). See above.
`NA_val`	The output matrix consists of ancestral rangesizes and rangesizes of the smaller descendant. Some values are disallowed – e.g. descendant ranges larger than the ancestor; or, in subset speciation, descendant ranges the same size as the ancestor are disallowed. All disallowed descendant rangesizes get `NA_val`.

To test different models, the user has to have control of the relative probability of different descendant rangesizes. The probability of each descendant rangesize could be parameterized individually, but we have a limited amount of observational data (essentially one character), so efficient parameterizations should be sought.

One way to do this is with the Maximum Entropy (Harte (2011)) discrete probability distribution of a number of ordered states. Normally this is applied (in examples) to the problem of estimation of the relative probability of the different faces of a 6-sided die. The input "knowledge" is the true mean of the dice rolls. If the mean value is 3.5, then each face of the die will have probability 1/6. If the mean value is close to 1, then the die is severely skewed such that the probability of rolling 1 is 99 other die rolls is very small. If the mean value is close to 6, then the probability distribution is skewed towards higher numbers.

Here in BioGeoBEARS, we use the same Maximum Entropy function to specify the relative probability of geographic ranges of a number of different rangesizes. This is merely used so that a single parameter can control the probability distribution – there is no MaxEnt estimation going on here. The user specifies a value for the parameter maxent_constraint_01 between 0.0001 and 0.9999. This can then be applied to all of the different ancestor-descendant range combinations in the cladogenesis/speciation matrix.

Example values of maxent_constraint_01 would give the following results:

maxent_constraint_01 = 0.0001 – The smaller descendant has rangesize 1 with 100 LAGRANGE)
maxent_constraint_01 = 0.5 – The smaller descendant can be any rangesize equal probability. This is effectively what happens in DIVA's version of vicariance speciation
maxent_constraint_01 = 0.9999 – The smaller descendant will take the largest possible rangesize for a given type of speciation, and a given ancestral rangesize. E.g., for sympatric/range-copying speciation (the ancestor is simply copied to both descendants, as in a continuous-time model with no cladogenesis effect), an ancestor of size 3 would product two descendant lineages of size 3. Such a model is implemented in the program BayArea (Landis et al. (2013)). LAGRANGE, on the other hand, would only allow range-copying for ancestral ranges of size 1.

Note: In LAGRANGE-type models, at speciation/cladogenesis events, one descendant daughter branch ALWAYS has size 1, whereas the other descendant daughter branch either (a) is the same (in sympatric/range-copying speciation), (b) inherits the complete ancestral range (in sympatric/subset speciation) or (c) inherits the remainder of the range (in vicariant/range-division speciation). LAGRANGE-type behavior (the smaller descendant has rangesize 1 with 100 rangesize) can be achieved by setting the maxent_constraint_01 parameter to 0.0001.

See also: Maximum Entropy probability distribution for discrete variable with given mean (and discrete uniform flat prior) http://en.wikipedia.org/wiki/Maximum_entropy_probability_distribution

Currently, the function maxent from the FD package is used to get the discrete probability distribution, given the number of states and the maxent_constraint_01 parameter. This could also be done with get_probvals, which uses calcZ_part, calcP_n, following equations 6.3-6.4 of Harte (2011), although this is not yet implemented.

relprob_subsets_matrix, a numeric matrix giving the relative probability of each rangesize for the smaller descendant of an ancestral range, conditional on the ancestral rangesize.

Go BEARS!

Nicholas J. Matzke matzke@berkeley.edu

http://phylo.wikidot.com/matzke-2013-international-biogeography-society-poster http://en.wikipedia.org/wiki/Maximum_entropy_probability_distribution

ReeSmith2008

Ronquist1996_DIVA

Ronquist_1997_DIVA

Harte2011

Landis_Matzke_etal_2013_BayArea

Matzke_2012_IBS

Ronquist_Sanmartin_2011

relative_probabilities_of_subsets, symbolic_to_relprob_matrix_sp, get_probvals, maxent, calcZ_part, calcP_n

testval=1
# Examples

# Probabilities of different descendant rangesizes, for the smaller descendant,
# under sympatric/subset speciation
# (plus sympatric/range-copying, which is folded in):
relative_probabilities_of_subsets(max_numareas=6, maxent_constraint_01=0.0001,
NA_val=NA)
relative_probabilities_of_subsets(max_numareas=6, maxent_constraint_01=0.5,
NA_val=NA)
relative_probabilities_of_subsets(max_numareas=6, maxent_constraint_01=0.9999,
NA_val=NA)

# Probabilities of different descendant rangesizes, for the smaller descendant,
# under vicariant speciation
relative_probabilities_of_vicariants(max_numareas=6, maxent_constraint_01v=0.0001,
NA_val=NA)
relative_probabilities_of_vicariants(max_numareas=6, maxent_constraint_01v=0.5,
NA_val=NA)
relative_probabilities_of_vicariants(max_numareas=6, maxent_constraint_01v=0.9999,
NA_val=NA)