We revisit the topics of near-field adaptive beamforming and source localization following an alternative approach based on a spatio- temporal spectral representation of the acoustic wave field. With the proposed method, the wave field is expressed as a separable combination of the signal and spatial components that characterize the various sources in the acoustic scene. This allows beamform- ing operations such as beam steering and sidelobe canceling to be translated into a two-dimensional (2D) sampling problem, where the sampling kernels are derived according to a parametric model repre- senting the 2D spectral pattern generated in the presence of a source. Conversely, the spectral pattern can be estimated from an arbitrary input through the use of parametric spectral estimation techniques, providing a novel solution to the near-field source localization prob- lem.