> tp_fsyl
class       : SpatialPolygonsDataFrame
features    : 149
extent      : -6.776647, 35.13454, 37.74027, 59.70762  (xmin, xmax, ymin, ymax)
coord. ref. : +proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0
variables   : 3
names       : Id,          layer.1,          layer.2
min values  :  0, 47.1897926634769, 510.438502673797
max values  :  0, 138.237654320988, 1339.66159594342

t_fsyl <- fortify(tp_fsyl, region="layer.1")

> head(t_fsyl)
      long      lat order  hole piece              group               id
1 17.03176 45.09981     1 FALSE     1 100.269953051643.1 100.269953051643
2 17.08139 45.06541     2 FALSE     1 100.269953051643.1 100.269953051643
3 17.10079 45.04859     3 FALSE     1 100.269953051643.1 100.269953051643
4 17.12986 45.02336     4 FALSE     1 100.269953051643.1 100.269953051643
5 17.11578 45.00132     5 FALSE     1 100.269953051643.1 100.269953051643
6 17.06936 44.98166     6 FALSE     1 100.269953051643.1 100.269953051643

> str(t_fsyl)
'data.frame':   11153 obs. of  7 variables:
 $ long : num  17 17.1 17.1 17.1 17.1 ...
 $ lat  : num  45.1 45.1 45 45 45 ...
 $ order: int  1 2 3 4 5 6 7 8 9 10 ...
 $ hole : logi  FALSE FALSE FALSE FALSE FALSE FALSE ...
 $ piece: Factor w/ 20 levels "1","2","3","4",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ group: Factor w/ 152 levels "100.269953051643.1",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ id   : chr  "100.269953051643" "100.269953051643" "100.269953051643" "100.269953051643" ...

ggplot(t_fsyl) + geom_polygon(aes(x=long, y=lat, fill=id))

ggplot(t_fsyl) + geom_polygon(aes(x=long, y=lat, fill=group))

library(rgdal)
library(raster)

#http://www.euforgen.org/fileadmin/templates/euforgen.org/upload/Documents/Maps/Shapefile/Fagus_sylvatica.zip
fsyl <- readOGR(dsn=".", layer="Fagus sylvatica")

#http://biogeo.ucdavis.edu/data/climate/worldclim/1_4/tiles/cur/bio_15.zip
#http://biogeo.ucdavis.edu/data/climate/worldclim/1_4/tiles/cur/bio_16.zip
#http://biogeo.ucdavis.edu/data/climate/worldclim/1_4/tiles/cur/bio_17.zip
temp1 <- raster("bio1_15.bil")
prcp1 <- raster("bio12_15.bil")

temp2 <- raster("bio1_16.bil")
prcp2 <- raster("bio12_16.bil")

temp3 <- raster("bio1_17.bil")
prcp3 <- raster("bio12_17.bil")

temp <- merge(temp1, temp2, temp3)
prcp <- merge(prcp1, prcp2, prcp3)

te_pr <- addLayer(temp, prcp)

projection(te_pr) <- CRS("+proj=longlat +datum=WGS84")

fsyl <- spTransform(fsyl, CRS(projection(te_pr)))

tp_fsyl <- extract(te_pr, fsyl, fun=mean, method="bilinear", sp=T)