You might consider using the union function from the raster package. The following example demonstrates how you can read in two polygon shapefiles and union them together. In this example, the first shapefile contains one polygon and the second contains three polygons.
##load libraries
library(rgdal)
library(raster)
Next read in your shapefiles using readOGR from rgdal
#read in first polygon shapefile
subs1 <- readOGR('sub1.shp')
#read in second polygon shapefile
subs2 <- readOGR('sub2.shp')
Run a summary to check that they have loaded correctly:
summary(subs1)
Object of class SpatialPolygonsDataFrame
Coordinates:
min max
x 563566.8 564092.6
y 613293.4 613595.3
Is projected: TRUE
proj4string :
[+proj=tmerc +lat_0=53.5 +lon_0=-8 +k=0.99982 +x_0=600000 +y_0=750000
+ellps=GRS80 +units=m +no_defs]
Data attributes:
SURVEY_YEA LAND_USE_T SPECIES_CO PLANTING_Y COM_SUB1
Min. :2008 CHF:1 NS:1 Min. :2003 12344A3:1
1st Qu.:2008 1st Qu.:2003
Median :2008 Median :2003
Mean :2008 Mean :2003
3rd Qu.:2008 3rd Qu.:2003
Max. :2008 Max. :2003
summary(subs2)
Object of class SpatialPolygonsDataFrame
Coordinates:
min max
x 563599.3 564704.3
y 612977.6 613588.5
Is projected: TRUE
proj4string :
[+proj=tmerc +lat_0=53.5 +lon_0=-8 +k=0.99982 +x_0=600000 +y_0=750000
+ellps=GRS80 +units=m +no_defs]
Data attributes:
SURVEY_YEA LAND_USE_T SPECIES_CO PLANTING_Y COM_SUB1
Min. :2010 CHF:3 SP:3 Min. :2002 12345A1:1
1st Qu.:2010 1st Qu.:2004 12345A2:1
Median :2012 Median :2005 12345B1:1
Mean :2011 Mean :2005
3rd Qu.:2013 3rd Qu.:2007
Max. :2014 Max. :2009
Generate a simple plot to show the spatial location of the features:
##plot the inputs:
plot(subs2, col='blue')
plot(subs1, add=TRUE, col='red')

Union the features:
##union the SpatialPolygonsDataFrame
subs_union <- union(subs1, subs2)
Check the output:
plot(subs_union, col='brown')

summary(them)so we can see what you've got (or share your shapefiles). Show us what you get when you try those methods. Show us code. Code is reproducible. – Spacedman Dec 05 '17 at 17:44