So, really, I just wrote a function in R to apply the jaccard similarity function to all possible pairs in a series of columns from a data frame and spit out the result in a matrix. I am pretty happy with myself.
here is the function and the results so you can now know how similar the group of observers that visit different habitats on the island of Grand Bahama were between 1988 and 2016.

Jaccardcolumns <- function(x,fun)
{
n <- ncol(x)

foo <- matrix(0,n,n)
for ( i in 1:n)
{
for (j in 1:n)
{
foo[i,j] <- fun(x[,i],x[,j])
}
}
colnames(foo)<-rownames(foo)<-c("Water", "Pine", "Wetland", "Sand", "Urban", "Grass", "HWTC")
return(foo)
}

Jaccardcolumns(ObserverVisitedHabitat[2:8], clujaccard)

> Jaccardcolumns(ObserverVisitedHabitat[2:8], clujaccard)
Water Pine Wetland Sand Urban Grass HWTC
Water 1.000 0.084 0.076 0.058 0.071 0.048 0.036
Pine 0.084 1.000 0.336 0.354 0.400 0.330 0.245
Wetland 0.076 0.336 1.000 0.463 0.362 0.360 0.217
Sand 0.058 0.354 0.463 1.000 0.420 0.496 0.193
Urban 0.071 0.400 0.362 0.420 1.000 0.389 0.216
Grass 0.048 0.330 0.360 0.496 0.389 1.000 0.163
HWTC 0.036 0.245 0.217 0.193 0.216 0.163 1.000

Ancilleno Davis, AA; BSc; MSc
Twitter: @ancilleno
Founder/Coordinator – BEINGS
Director At Large – BirdsCaribbean