Fish populations in continental shelf environments can be continuously imaged over thousands of square kilometers using acoustic waveguide remote sensing techniques [Makris etal., Science, Feb. (2006)]. A calibrated range‐dependent scattering and reverberation model [Ratilal etal., J. Acoust. Soc. Am. 114, 2302 (2003)] based on the parabolic equation has been applied to assess population densities of fish by inverting long‐range acoustic data collected on the New Jersey continental shelf. This model is now applied to predict the types of fish species and zooplankton that are detectable in a general range‐dependent continental shelf environment, including the resolution and accuracy that can be expected in estimating fish population densities and for differentiating fish species. We consider different geometries of the source and receiving array to enhance biological detection and reduce background reverberation in highly range‐dependent environments. Using multiple source frequencies, the possibility of distinguishing fish species based on their differing scattering characteristics and resonance frequencies will be examined.