Data from: Model selection in historical biogeography reveals that founder-event speciation is a crucial process in island clades
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https://datadryad.org/dataset/doi:10.5061/dryad.2mc1t
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Founder-event speciation, where a rare jump dispersal event founds a new
genetically isolated lineage, has long been considered crucial by many
historical biogeographers, but its importance is disputed within the
vicariance school. Probabilistic modeling of geographic range evolution
creates the potential to test different biogeographical models against
data using standard statistical model choice procedures, as long as
multiple models are available. I re-implement the
Dispersal-Extinction-Cladogenesis (DEC) model of LAGRANGE in the R package
BioGeoBEARS, and modify it to create a new model, DEC+J, which adds
founder-event speciation, the importance of which is governed by a new
free parameter, j. The identifiability of DEC and DEC+J is tested on
datasets simulated under a wide range of macroevolutionary models where
geography evolves jointly with lineage birth/death events. The results
confirm that DEC and DEC+J are identifiable even though these models
ignore the fact that molecular phylogenies are missing many cladogenesis
and extinction events. The simulations also indicate that DEC will have
substantially increased errors in ancestral range estimation and parameter
inference when the true model includes +J. DEC and DEC+J are compared on
13 empirical datasets drawn from studies of island clades. Likelihood
ratio tests indicate that all clades reject DEC, and AICc model weights
show large to overwhelming support for DEC+J, for the first time verifying
the importance of founder-event speciation in island clades via
statistical model choice. Under DEC+J, ancestral nodes are usually
estimated to have ranges occupying only one island, rather than the
widespread ancestors often favored by DEC. These results indicate that the
assumptions of historical biogeography models can have large impacts on
inference and require testing and comparison with statistical methods.
提供机构:
Dryad
创建时间:
2014-07-29



