Carl Boettiger

Sim­u­la­tions com­pleted, help accen­tu­ate the dif­fer­ent paths for branch­ing.  When the most fail­ures occur while wait­ing for the first muta­tion to enter first estab­lished dimor­phism, muta­tion rate seems lim­it­ing (left): (right) With a higher muta­tion rate, most col­lapses back to monomor­phism occur after a muta­tion suc­cess­fully invades in the dimor­phic pop­u­la­tion. Unfor­tu­nately these runs result in …

My last post was a bit pes­simistic, some­times I can still miss the for­est for the trees.  Hid­den in those fig­ures, the main point has been star­ing me in the face.  So let’s try this again. Sto­chas­tic lim­its to evo­lu­tion­ary branch­ing is the story of two duel­ing timescales.  The first timescale is that of the evo­lu­tion­ary …

Ran a series of sim­u­la­tions overnight to explore aspects of time-to-branching at dif­fer­ent phases of the branch­ing process.  Still using only 16 repli­cates per data point, though increased max­i­mum time for a run another order of mag­ni­tude to avoid tim­ing out runs influ­enc­ing the dataset for the slow-rate para­me­ters.  Still seems to sug­gest a regime …

Set­ting up some adap­tive dynam­ics sim­u­la­tions to com­plete the parameter-space search.  Cur­rently the demo library con­tains two files, pro­vid­ing the coexistence-only tests and the full evo­lu­tion­ary sim­u­la­tion.  This picks up from Aug 30/Sept 1 on coex­is­tence times and Aug 12/13 entries on wait­ing times until branch­ing (while still on OWW). coex­is­tence times coexist_times.R cre­ates con­tour plots of …

Adap­tive dynam­ics is a set of recently devel­oped tech­niques for under­stand­ing phe­no­typic evo­lu­tion, using a dynam­i­cal sys­tems approach to con­cepts from evo­lu­tion­ary game the­ory. In con­trast to pop­u­la­tion genet­ics, this approach tends to explore richer eco­log­i­cal inter­ac­tions and sim­pler genetic assump­tions, with sig­nif­i­cant con­tro­versy. My own work has focused on a par­tic­u­lar ele­ment of the …