mebioda

Topological analysis

G-D Yang, P-M Agapow & G Yedi, 2017. The tree balance signature of mass extinction is erased by continued evolution in clades of constrained size with trait-dependent speciation. PLoS ONE 12(6): e0179553 doi:10.1371/journal.pone.0179553

• What happens to the signatures of mass extinctions or radiations (such as imbalance or “stemminess”)?
• Wouldn’t they eventually be swamped?
• What can we learn from simulation?

Experimental evolution using Avida

Avida is a free, open source scientific software platform for conducting and analyzing experiments with self-replicating and evolving computer programs. It provides detailed control over experimental settings and protocols, a large array of measurement tools, and sophisticated methods to analyze and post-process experimental data.

Effect on tree balance of mass extinction

Change in tree balance at select time points after mass extinction episode in communities of avida digital organisms.

• Mass extinction treatments were applied randomly and instantaneously (pulse) or by massive environmental change over a period of time (press), at strong and weak intensities.
• The y-axis is Aldous’s β [β_A] a measure of tree balance applicable to non-dichotomous trees; a Yule expectation is around zero, while more negative values indicate trees more imbalanced than this expectation.
• Data points are averages of 100 replicates ± 2 standard errors. Solid traces are maximum likelihood estimates of β_A, dashed traces are 95% confidence intervals around the calculated β_A estimates. β_A values (with confidence intervals) were determined using a customized version of the maxlik.betasplit function in the R package apTreeshape (courtesy M. Blum).

Tree simulation using MeSA

• The Avida analyses imply a “recovery” model until saturation, which might swamp sooner
• There is no facility to explore traits interacting with diversification
• More can be accomplished by scripting tree simulations in MeSA

Exemplar phylogenetic trees showing change in balance and trait/rate values over time. Branch lengths are scaled in MeSA absolute time. Tips are coloured according to trait value ranges shown in colour scale at bottom.

• a) t = 165, trait variance approximately 1, increasing
• b) t = 320, trait variance at half-maximum, increasing
• c) t = 400, maximum variance
• d) t = 420, half-maximum, descending
• e) t = 520, variance < 1 but still strong imbalance, descending.
• f) t = 600, variance at end-simulation

Parameterization of the extinction events

Three mass extinction treatments were employed:

• Random = taxa were culled from the tree regardeless of trait value or phylogenetic position.
• Selective-on-diversifiers = taxa culled from the tree had the lowes trait value and highest speciation rates.
• Selective-on-relicts = those taxa with highest trait value and lowest speciation rates were culled preferentally.

Each of the treatments occurred at intensity:

• 90%
• 75%
• 50% of all the extant taxa in the tree

Post-simulation analysis

• NEXUS files produced by MeSA were then manipulated in R to compute I_c values using the function colless for each tree in a time series and treatment MESA_output files
• The treatments were coded as:
  • RAND = random extinction
  • SOD = selective-on-diversifiers
  • SOR = selective-on-relicts
  • 0.5, 0.75, and 0.9 refer to extinction intensity
• Short-dashed lines above and below the zero line indicate boundaries of inner Yule zone; long-dashed lines indicate outer Yule zone boundaries.
• For the three treatments combined with the different intensities and the control, I_c values were collected at points:
  • PRE-EXT = pre extinction time (300)
  • CSR = clade-size recovery
  • CSR/END 1QTR = simulation first-quarter
  • CSR/END MID = midpoint
  • CSR/END 3QTR = three-quarter point
  • END SIM = at the end of simulation (600)
• In addition, values were collected at:
  • post extinction event (305)
  • at the CSR end-mid time (470)

Hypothesis tests

• I_c values were later rearranged in EXCEL and exported in txt files to be used for the statistical analyses.
• The treatments involving a combination of extinction types and intensity were analyzed with two-way ANOVA and Tukey-corrected multiple comparison testing, in order to see if there are any significant treatment-by-intensity interactions.
• To test whether the various extinction treatment outcomes differed systematically from the control and pre-treatment reference points, Dunnett’s tests were perfomed, using either pre-treatment or the control treatment as the reference standard.

“We cannot solely use tree balance metrics to infer past history of mass extinction for a given extant clade’s phylogeny. […] our results are a further demonstration that as an evolving clade gets further away from a mass extinction event, subsequent evolution can obscure and eventually erase the initial phylogenetic effects caused by the extinction/recovery process.”

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