Novel Covariance-Based Neutrality Test of Time-Series Data Reveals Asymmetries in Ecological and Economic Systems
Fig 1
Conceptual map of covariance-testing.
(A) The dynamics of a 15-species neutral community of 10,000 individuals and migration probability m = 0.0002 (shown here) can be approximated by a WFP with λ = 20 (see eq 1). If the community is neutral, then the CVTs should yield homoskedastic plots of νt versus ft. We test neutrality by randomly drawing from the 2n possible CVTs, performing homoskedasticity tests on νt versus ft, and then testing the uniformity of the resulting P-value distribution using a modified KS-test (see details in S1 Text, part 3). (B) The relative abundances of 15 independent, mean-reverting geometric brownian motions, d log Xt = μ(b − log Xt)dt + σdWt with μ = 15, σ = 30, b = 10. Neutrality is rejected by the highly non-uniform distribution of P-values. The left-skewed P-value distribution indicates many CVTs had volatilities that depended on the state variable, ft.