How to interpret Random Forest variable importance vs. distribution of min depth plots?

I am using Random Forest (regression) to analyze data on civil conflict. I have plotted two different things: variable importance and the distribution of the min depth (using the package randomForest randomForestExplainer in R).

My question is: How come the variable with the highest variable importance is not the variable with the lowest mean min depth? And what does this mean that they are not equal? I included the two images.

The dependent variable is conflict intensity. The data is structured in a country-year format, so for every country I have a data-point for every year. The independent variables include population, region, gdp etc.

require(randomForest)

require(randomForestExplainer)

randomF <- randomForest(max_intensity ~ nrgroups + GDPlog_lag + logPopulation + Polity_lag + Asia + Africa + MiddleEast + Europe + Americas, data=MAR_regressions, na.action=na.exclude)

plot(randomF, type="l", main= "Random Forest Protest and Rebellion")

varImpPlot(randomF, main="Variable Importance Random Forest Prot & Reb", col="blue")

plot_min_depth_distribution(randomF)