Modern Cetaceans

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Modern cetacean data has been used as a model of macroevolution due to its remarkable fossil record. The palaeodiversity of whales has been associated with environmental factors such as relative abubndances of diatom, δ18O isotopic measurement and nannoplankton abundances. The diversification rate are thought to suggest an early rapid burst diversification associated with adaptive radiation while the rate shifts are thought to locate the rate shifts in the phylogenetic tree. Here, these three areas are investigated using means of algorithms that allow to test for correlation between two variables and more importantly calculate the log-likelihood using maximum likelihood method and Akaike Information Criterion (AIC). Phylogenetic signal is considered …show more content…
The widely known transition from terrestrial Archaeocete (ancient whales) to riverine and shallow marine settings to open oceans have been extensively researched [6]. However, modern whales can be independently assessed from their ancestors because there have been no archaeocete-like fossils found in the clade Neoceti, comprising modern whales and dolphins, despite their similar morphology [6].
The fossil records of cetaceans are distributed across the globe within a wide latitudinal range (Figure 1). The drivers of palaeodiversity of the cetaceans have long been associated with extrinsic factors associated with the chemistry of the ocean as well as availability of food [2].
In this report, the macroevolution of cetacean, with primary focus on whales, are explained by quantitative assessments of palaeodiversity drivers to understand the diversification of whales since they first appeared as well as if extrinsic factors drive their diversity as suggested with consideration of quality of fossil record to eliminate biasness when possible. In addition, patterns of trait evolution and lineage
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The best-fitted model is represented by the Brownian Motion (BM) although the AIC value is lower than that of delta model. This is because after likelihood test between BM model and the delta model, the probability value returns with a result of 0.101 (p<0.05) and therefore, the delta fit cannot be assumed to be better fit than that of BM (Table 5). This suggests that the evolutionary model which may suit best with the observed calculation is that, whales evolved in a random manner with constant evolutionary rate. This is tested again, using Ornstein-Uhlenbeck to account for random walks but calculation in the end, suggests that in fact, the evolutionary rate of whales should follow BM model and indeed, random walk is not appropriate here. So, trait evolved