Designing with Uncertainty: A Probability Space Method for Range-Based Anticipation in Biodesign

Abstract Biologically derived materials, such as fungal systems, challenge conventional design approaches because their properties emerge through interactions between organism and environment rather than being predetermined. This introduces significant uncertainty in early-stage design, where decisions must be made before full fabrication outcomes are known. This paper presents an experimental study using Pleurotus ostreatus to examine relationships between environmental parameters, including humidity, CO₂ concentration, gravitational orientation, and substrate volume, and resulting morphological variation. Through single- and multi-parameter cultivation experiments, the study identifies consistent patterns of nonlinear response, directional correlation, and threshold effects in growth outcomes. From analysis of these experimental results, the paper derives the Probability Space Method (PSM ) , a representational framework that emerges from observed variability. PSM structures empirical data into bounded spatial representations of likely morphological outcomes. It does not function as a predictive or mechanistic model, but as a designer-facing system for organising uncertainty into navigable fields of possibility. The method is further developed through 2D and volumetric visualisations that map relative likelihoods of morphological occurrence in space. Results show that most observed outcomes fall within predicted ranges derived from prior experiments, suggesting that biological variability can be structured for early-stage design reasoning under conditions of limited data.