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Abstract Small microphone arrays and sound‐source localisation algorithms are increasingly prevalent in the passive acoustic monitoring (PAM) of ecosystems. These technologies enable analysis of natural soundscapes' spatial features, yielding additional insights into biodiversity and ecosystem health. While many of these technologies have been evaluated in the field, there is a lack of controlled, repeatable methods to test them. We developed an ambisonic virtual sound environment (VSE) for simulating real natural soundscapes to evaluate spatial PAM technologies. We validated this novel approach using a PAM recorder with a six‐microphone array, from which we extracted a typical suite of ecoacoustic metrics, including acoustic indices and avian species predictions and localisations from the software BirdNET and HARKBird, respectively. We first verified whether the VSE could replicate natural soundscapes well enough to test PAM technologies by comparing these metrics between field and VSE‐based recordings. To pilot the VSE as an environment for testing PAM hardware, we assessed how orientation impacts the six‐microphone array's performance by using the same suite of metrics to compare VSE recordings made with the array at various pitch angles. Finally, we piloted the VSE as a test platform for PAM software by investigating how BirdNET and HARKBird perform on bird calls added to the VSE‐replicated soundscapes. While the VSE and field recordings had similarities in some metrics, including spectral composition and BirdNET predictions, ambisonics' perceptual bias and susceptibility to spatial aliasing limited the spatial analyses that could be undertaken. Our trials nonetheless revealed that device orientation impacts the performance of HARKBird and certain ecoacoustic indices, and that BirdNET and HARKBird perform best on louder, more directional bird calls. Our results demonstrate the potential for this approach, but highlight limitations to using an ambisonics‐based VSE. We thus provide guidelines for the use and refinement of such systems towards more standardised, controlled benchmarking of PAM technologies, empowering practitioners to make more informed decisions on using these vital tools.