Only recently has haplotype reconstruction been considered for population-sampled short read data. We discuss a new software tool, Hapler, for this problem. Hapler is designed specifically for low-diversity, low-coverage datasets, such as ecological samples of eukaryote populations. Since such datasets may contain errors as well as ambiguous haplotype information, we develop methods to limit results to high-confidence reconstructions. Simulated sequencing and reconstruction of sample data suggests that Hapler is effective, and its effectiveness will increase as sequencing technologies continue to produce longer reads and lower error rates.