ggmap, hexbin and length distortion in Lat/long

I am working with spatial data in ggmap, generally with great success.
I have a huge data set with the coordinates in NAD 83 UTM Zone 11
(meters).  To map the data the coordinates were converted to Lat Long
in GIS prior to use in R and ggmap/ggplot. I am using hexagonal binning
to aggregate the data :
#create bins and calculate stats

hb<-hexbin(DF$lon,DF$lat,xbins=80,IDs=TRUE)
hb.avg<-hexTapply(hb,DF$Res,mean,na.rm=TRUE)
hb.mx<-hexTapply(hb,DF$Res,max,na.rm=TRUE)
hb.p80<-hexTapply(hb,DF$Res,quantile,prob=0.80,na.rm=TRUE)
#create df for ggplot
hx_dat <- data.frame(hcell2xy(hb), count = hb at count,
   xo = hb at xcm, yo = hb at ycm, Mean=hb.avg,Max=hb.mx,
   p80=hb.p80)

#Base Map
#BBox is the bounding box
Base<-get_map(BBox,source='google')
m_hx<-ggmap(Base,legend = "bottom",
base_layer=ggplot(aes(x=x,y=y),data=hx_dat))
#Map of means
a<-0.55
hc<-'grey60'

m_hx+geom_hex(aes(x = x, y = y, fill = Mean),
 color = hc, ,alpha=a,stat = "identity") +
 scale_fill_gradientn("Mean",colours=rev(rainbow(4)),trans='sqrt')

...and so on for other stats
I can also run statistical analyses on hx_dat.
By creating hexbins based on lat/long it seems there will be distortion
due to the differences in length of a degree at different locations on
the earth's surface. What is the most efficient way to eliminate this
distortion? Should I run hexbin in NAD83 and convert the x/y
coordinates to Lat Long? Can I get ggmap to convert the baselayer to
NAD84 and just do everything in NAD(my preferred option)?
I have tried converting Lat Long to NAD84 and back but the coordinates
are coming up in the eastern Pacific and not in California, so I am
missing something and I am not sure that is the best way to solve the
problem anyway. Thanks in advance, any help is greatly appreciated
Mike

Michael J. Bock, PhD | Senior Manager
mbock at environcorp.com