The availability of genome-wide sequence data from many species and individuals within species has ushered in the era of phylogenomics. In this era, species phylogeny inference is based on models of sequence evolution on gene trees and models of gene tree evolution within species phylogenies. All existing inference methods, except parsimony, assume a common mechanism across loci as represented by unvarying branch lengths of the species phylogeny. In this thesis, we propose a ``no common mechanism" (NCM) model, in which the parameters of the species phylogeny may vary between loci. We derive an analytically integrated likelihood of species networks given gene trees from multiple loci under an NCM model. We demonstrate the performance of inference under this integrated likelihood on simulated and biological data. The model presented here will afford opportunities for exploring connections among various methods for estimating species phylogenies from multiple, independent loci.