Estimation of species range fragmentation
Very interesting question +1. I don't know the literature on the subject very well but I did not find much by looking for it. I know that a number of methods exist when you have genetic data (STRUCTURE or some of the work of J. Novembre probably).

Here are two possible solutions

Fitting $x$ distributions

You could be fitting 1, 2, 3, ...., n normal (or uniform) distributions to the observed data. Each time, compare their maximum likelihood (for which you might need a MCMC with 2⋅x parameters, where $0≤x≤n$ is the number of distributions you're fitting) and select the "best" model with some information criterion such as AIC or BIC.

The number of fragments is just the $x$ value associated with the lowest AIC.

Logistic regression

Another (faster and simpler) solution would be to fit a logistic regression to your data.

Iteratively fit a logistic regression of degree 1,2,3,...n and then again use some information criteria to select the 'best'.

To find the number of fragments, you can then either use the number of degrees in the model or even better use some threshold on the the probability of getting a zero (which you could compute with the package effects in R).

Notes

It will probably takes you a day or so if you're at ease with these methods and have intro knowledge in programming.

You might want to get opinions from stats.SE as well.