Abstract
Abstract
Bioinspiration and biomimetics rely on biological diversity to generate novel design solutions, yet research remains heavily biased toward a small number of well-studied model organisms, often limiting innovation to incremental advances. A major challenge lies in determining how much biodiversity must be sampled to effectively capture the range of morphologies relevant to biological function and extract design principles. Here, we use echinoid (sea urchin) spine microarchitectures as a case study to quantify how biodiversity sampling influences the morphospace, a quantitative representation of morphological diversity. Micro-computed tomography data were collected from 177 species, representing ∼50% of total regular non-cidaroid echinoid diversity, with systematic coverage across all taxonomic levels. Mimetica, an open-source Python package, was developed to extract and analyse radial and phase profiles that define spine microarchitecture from two-dimensional image stacks. Morphospace analysis revealed rapid saturation: approximately 50% of the morphospace was recovered by sampling 20% of morphotypes—distinct spine microarchitectures, typically one per species—with diminishing returns at higher sampling. The morphospace was largely defined by a small subset of morphotypes that shape the boundaries of the convex hull, concentrated in relatively few genera, while most species contributed negligibly to overall hull volume. Sampling a single morphotype per genus recovered ∼72% of the morphospace, demonstrating that broad taxonomic coverage is sufficient to capture major axes of variation, while exhaustive species-level coverage adds little benefit. Our results provide the first empirical evidence that opportunistic, low-diversity sampling is insufficient to recover the full extent of morphological variation. Systematic, taxonomically informed sampling, rather than a focus on individual species, is essential for capturing the diversity that underpins biomimetic and bioinspired innovation. Additionally, future research should prioritize the identification of morphologically extreme, convex hull-defining taxa, as these approximate the limits of morphological variation and are more likely to translate into distinct functional outcomes.