Coupling abundance and spatial distribution for an unbiased and tractable beta diversity framework

While fundamental for understanding community assembly, dominant beta diversity metrics suffer from severe sample-size dependence and lack tractable generative predictions. Here, we generalize Whittaker’s multiplicative index into a novel abundance-weighted framework. By proving this index strictly equals the expectation of the Good-Turing sample coverage deficit, we unify species abundance and spatial occupancy into a single, design-unbiased parameter. Furthermore, deriving exact neutral expectations provides process-based baselines to dissect beta diversity’s internal structure via additive decomposition into species (SCBD) and local (LCBD) contributions. Application to two large-scale forest plots empirically validates its strict sampling invariance and reveals non-neutral signatures. Crucially, our SCBD diagnostic reveals a striking ecological phase transition: rare-to-intermediate species are more spatially scattered than neutral drift predicts until reaching an aggregation onset threshold, beyond which dominant species exhibit supra-neutral aggregation, reflecting competition-colonization trade-offs. Concurrently, LCBD diagnostics successfully isolate the spatial footprints of environmental filtering from pervasive neutral noise. By avoiding the conflation of statistical estimation bias from genuine biological scaling and anchoring metrics in tractable models, this framework provides a rigorous toolkit that transforms our empirical understanding of spatial coexistence.