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#convert kilograms to grams
data_primates$Mass_gm = data_primates$Mass_kg*1000
#take the natural logarithm of grams
data_primates$Log_Mass_gm = log(data_primates$Mass_gm)

Take a look at the two new columns of data you added to your dataframe:

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Then call "brownian". R will print the following

 

 

$Trait1
$Trait1$lnl
[1] -30.98123
$Trait1$beta
[1] 0.02371125
$Trait1$aic
[1] 65.96246
$Trait1$aicc
[1] 66.27825
$Trait1$k
[1] 2

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trend = fitContinuous(tree_primates, data_primates$Log_Mass_gm,model="trend") 
 

If you type "trend," R will return to the command line:

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pchisq(0.22,1,lower.tail=F)

 

R will print
[1] 0.6390399

 

So, the p-value associated with this difference in log likelihoods is not significant, and we do not have evidence that a Brownian model of evolution should be rejected in favor of one with a directional trend.

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