`Q-niche': topology-preserving niche hypervolumes built using a quantum mechanics modelling analogue.

Q-niche, a quantum-mechanics-inspired hypervolume estimator, preserves non-convex niche topology more consistently than Gaussian kernel density estimation and one-class support vector machine across synthetic benchmarks.

• Why it matters: Estimating ecological niche hypervolumes from finite occurrences is difficult when niches have separated regions or internal holes, where standard estimators can distort structure.
• What they did: Q-niche uses an inverse Schrodinger formulation to convert an occurrence-derived Gaussian field into a potential surface, defining hypervolume via a stochastic point cloud.
• The result: In synthetic, virtual-species, and empirical Acacia analyses, inferred hypervolume size and topology were estimator-dependent; stronger topology preservation did not necessarily increase overlap with known geography.

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